{
  "schemaVersion": 2,
  "name": "looprepo",
  "publisher": "looprepo",
  "description": "A directory of copy-paste AI agent loops for Claude Code and Codex. Every loop carries a Safety Score (A-F) graded by a default-fail evaluator: exit conditions, iteration budgets, verification checks, scoping, and human gates.",
  "url": "https://looprepo.dev",
  "catalogUrl": "https://looprepo.dev/catalog.json",
  "plainTextUrl": "https://looprepo.dev/catalog.txt",
  "agentInstructionsUrl": "https://looprepo.dev/llms.txt",
  "agentGuideUrl": "https://looprepo.dev/agents",
  "mcpUrl": "https://looprepo.dev/api/mcp",
  "usage": "Read fresh data here — do not rely on memory or the paginated directory. Fetch catalog.json for structured selection, then fetch the loop `url` for the full prompt and safety notes. Prefer loops graded A or B. Never invent missing project details.",
  "updated": "2026-07-05T17:29:11.094Z",
  "loopCount": 212,
  "categories": [
    "testing",
    "ci",
    "docs",
    "security",
    "refactoring",
    "performance",
    "devops",
    "database",
    "git",
    "review",
    "planning",
    "automation",
    "maintenance",
    "debugging",
    "quality",
    "evaluation",
    "content",
    "design"
  ],
  "loopTypes": [
    "loop",
    "goal",
    "schedule",
    "ralph"
  ],
  "agents": [
    "claude-code",
    "codex",
    "cursor",
    "aider",
    "cline",
    "windsurf"
  ],
  "loops": [
    {
      "slug": "sprint-plan-from-issues",
      "title": "Draft a sprint plan from the backlog",
      "url": "https://looprepo.dev/loops/sprint-plan-from-issues",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "sprint",
        "estimation",
        "backlog"
      ],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Turn the open issue backlog into a proposed two-week sprint plan with estimates, a dependency ordering, and an explicit cut line, written as a document for the team to edit.",
      "prompt": "/goal SPRINT-PLAN.md contains a proposed 2-week plan — read all open issues labeled `ready`, estimate each as S/M/L based on the code it touches, order them by dependency and value, draw a cut line at a realistic capacity, and list what falls below it with reasons; make no changes to the issues themselves; stop after 6 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The output is a proposal document, not tracker mutations, so planning authority stays with the team. Estimates grounded in the actual code beat gut-feel sizing.",
      "upvotes": 0,
      "copies": 1,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "check-the-pr-every-15-min",
      "title": "\"check the PR every 15 min\" |",
      "url": "https://looprepo.dev/loops/check-the-pr-every-15-min",
      "loopType": "schedule",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "damian87x",
        "authority": 40,
        "githubStars": null
      },
      "description": "Community schedule loop for ci, sourced from github. Verified exit condition, evaluator-gated.",
      "prompt": "/schedule \"check the PR every 15 min\" |",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "damian87x",
        "url": "https://github.com/damian87x/oh-my-copilot"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "get-auth-tests-green",
      "title": "Get auth tests green",
      "url": "https://looprepo.dev/loops/get-auth-tests-green",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "invincible04",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run auth tests and linter until all pass and the diff is clean.",
      "prompt": "/goal All tests in test/auth/ pass, lint is clean, and the diff touches only",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "invincible04",
        "url": "https://github.com/invincible04/awesome-loop-engineering/blob/c49c2d85d0748d4eb35e1ac19d9bbce4f7a518c1/prompts/goal-and-loop.md"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "ship-a-pr-through-ci-and-reviews",
      "title": "Ship a PR through CI and reviews",
      "url": "https://looprepo.dev/loops/ship-a-pr-through-ci-and-reviews",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "gmickel",
        "authority": 40,
        "githubStars": null
      },
      "description": "Draft a PR, run CI, collect reviews, merge, and release—repeat every 30 minutes until land criteria are met.",
      "prompt": "/loop 30m /flow-next:land # ship loop: draft PR → CI green → reviews converged → merged → released",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "gmickel",
        "url": "https://github.com/gmickel/flow-next"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "ship-specs-through-code-review",
      "title": "Ship specs through code review",
      "url": "https://looprepo.dev/loops/ship-specs-through-code-review",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "gmickel",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run spec-driven workflow loop every 10 minutes: plan work, collect reviews, execute tasks, open pull requests.",
      "prompt": "/loop 10m /flow-next:pilot # build loop: ready spec → plan → reviews → work → draft PR",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "gmickel",
        "url": "https://github.com/gmickel/flow-next"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "run-detect-fix-verify-cycles",
      "title": "Run detect-fix-verify cycles",
      "url": "https://looprepo.dev/loops/run-detect-fix-verify-cycles",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "community",
        "label": "chasecjj",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run detect-fix-verify cycles up to 3 times until integration issues resolve.",
      "prompt": "/loop integration). Manages detect→fix→verify cycle with max 3 iterations",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "chasecjj",
        "url": "https://github.com/chasecjj/healing-hearts-website/blob/d745b660736876b8474c86dad5bb206912294ecd/.dispatch/tasks/agentic-qa-loop-arch/design-checklist.md"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "watch-pr-checks-pass",
      "title": "Watch PR checks pass",
      "url": "https://looprepo.dev/loops/watch-pr-checks-pass",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "EELeon",
        "authority": 40,
        "githubStars": null
      },
      "description": "Poll GitHub PR checks every 5 minutes until all status checks pass.",
      "prompt": "/loop 5m gh pr checks 1234",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "EELeon",
        "url": "https://github.com/EELeon/Claude-harness/blob/bb0f33a8858d9f82797625ca099278ab6d606759/README.md"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "re-run-pr-review-on-schedule",
      "title": "Re-run PR review on schedule",
      "url": "https://looprepo.dev/loops/re-run-pr-review-on-schedule",
      "loopType": "schedule",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "pricci1",
        "authority": 40,
        "githubStars": null
      },
      "description": "Re-invoke a specific PR review skill every 20 minutes until the review completes or you stop it.",
      "prompt": "/loop 20m /review-pr 1234 , to re-run that skill each iteration. {/ min-version: 2.1.196 /}As of v2.1.196, a scheduled fire only runs skills that Claude is [allowed to invoke on its own](/en/skills#control-who-invokes-a-skill). The following reach Claude as plain text instead of executing",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "pricci1",
        "url": "https://github.com/pricci1/cc-docs-changelog/blob/e1af1987b272d568f7b1ee987b7d12327e0fab74/docs/scheduled-tasks.md"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "run-agent-turns-until-goal-met",
      "title": "Run agent turns until goal met",
      "url": "https://looprepo.dev/loops/run-agent-turns-until-goal-met",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "Fchery87",
        "authority": 40,
        "githubStars": null
      },
      "description": "Agent executes repeated turns toward a condition, with a lightweight evaluator checking progress after each turn until the goal is reached.",
      "prompt": "/goal <condition turns a prompt into a durable objective. Thanos immediately starts a turn toward the condition, and after each turn a fresh, tool-less side-channel evaluator (a one-shot completeSimple call, not a subagent — so no extra agent turn and no re-entrancy) reads the last turn's evidence and returns MET / NOT MET . NOT MET auto-continues another turn with the reason as guidance; MET clears the goal and records the achievement. Unparseable evaluator output is treated as NOT MET (fail-safe: it never declares a false \"done",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Fchery87",
        "url": "https://github.com/Fchery87/thanos"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "run-workflows-with-dynamic-sub-agents",
      "title": "Run workflows with dynamic sub-agents",
      "url": "https://looprepo.dev/loops/run-workflows-with-dynamic-sub-agents",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "@daniel_mac8",
        "authority": 40,
        "githubStars": null
      },
      "description": "Split a task into packets, run sub-agents in parallel, synthesize results, and verify completion.",
      "prompt": "/goal loop and verify until complete",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "@daniel_mac8",
        "url": "https://x.com/daniel_mac8/status/2060390438557684200"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "make-all-tests-pass",
      "title": "Make all tests pass",
      "url": "https://looprepo.dev/loops/make-all-tests-pass",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "bytedance",
        "authority": 40,
        "githubStars": null
      },
      "description": "Implement remaining code and run tests repeatedly until the full suite passes.",
      "prompt": "/goal finish the implementation and make all tests pass",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "bytedance",
        "url": "https://github.com/bytedance/deer-flow"
      },
      "published": "2026-07-05"
    },
    {
      "slug": "schedule-batch-jobs-with-dapr-bindings",
      "title": "Schedule batch jobs with Dapr bindings",
      "url": "https://looprepo.dev/loops/schedule-batch-jobs-with-dapr-bindings",
      "loopType": "schedule",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "OneUptime",
        "authority": 40,
        "githubStars": null
      },
      "description": "Schedule recurring batch jobs and cleanup tasks using Dapr cron bindings, running on your defined cadence.",
      "prompt": "/Schedule | bindings.cron | Batch jobs, cleanup tasks |",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "OneUptime",
        "url": "https://github.com/OneUptime/blog/blob/ef9de1260838013b091ec96a00dde082f588b7b6/posts/2026-03-31-dapr-bindings-serverless-triggers/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "wire-up-c2-lsp-container-semantics",
      "title": "Wire up C2 LSP container semantics",
      "url": "https://looprepo.dev/loops/wire-up-c2-lsp-container-semantics",
      "loopType": "loop",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "shoedog",
        "authority": 40,
        "githubStars": null
      },
      "description": "Continuously verify and adjust C2's fetch, LSP environment, and cache mounts until container semantics validate correctly.",
      "prompt": "/loop semantics — the verify→review→tweak loop, ContainerRw lifecycle, reaping, merge hand-off are unchanged; C2 makes the fetch/verify/lsp env + commands + cache mounts + image language-selected",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "shoedog",
        "url": "https://github.com/shoedog/a2acp/blob/256d3568b537b3f8d22e2968c5a6846f10f54ec1/docs/superpowers/specs/2026-06-15-lsp-mcp-slice-c2-design.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-the-build-green-between-tasks",
      "title": "Keep the build green between tasks",
      "url": "https://looprepo.dev/loops/keep-the-build-green-between-tasks",
      "loopType": "goal",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "vitorfhc",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run tests and fix broken messages until all checks pass, then move to the next task.",
      "prompt": "/goal messages; this minimal edit keeps it green between tasks",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "vitorfhc",
        "url": "https://github.com/vitorfhc/BotDoBolao/blob/ecbcdfd58f46726394c6c106a96dab0c3e8b84f4/docs/superpowers/plans/2026-06-15-kickoff-goal-notifications.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-memory-pins-under-control",
      "title": "Keep memory pins under control",
      "url": "https://looprepo.dev/loops/keep-memory-pins-under-control",
      "loopType": "schedule",
      "category": "maintenance",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "kagura-ai",
        "authority": 40,
        "githubStars": null
      },
      "description": "Audit and prune pinned memory contexts to stay under 7, replacing competing invariants atomically and checking load count before each pin.",
      "prompt": "/goal that must load every session (it is then surfaced deterministically by load pinned ). Pin sparingly — keep a context at ≤7 pinned (prune at 10; the pinned load cap of 100 is a safety net, not the budget). Decisions/patterns/status are NOT pin material. Before pinning, call load pinned to check the count; when an invariant supersedes an old one, unpin the old in the same step ( update memory(memory id=<old , delivery mode=\"on recall\") ) so two competing invariants are never both pinned",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "kagura-ai",
        "url": "https://github.com/kagura-ai/memory-cloud/blob/fc36be308de9558d92c636a27467fd086e5bce9d/plugins/kagura-memory/skills/kagura-memory/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "park-loop-on-background-process",
      "title": "Park loop on background process",
      "url": "https://looprepo.dev/loops/park-loop-on-background-process",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "Signmanal",
        "authority": 40,
        "githubStars": null
      },
      "description": "Pause loop execution while a background process runs, then auto-resume when it exits.",
      "prompt": "/goal wait <pid [reason] | Park the loop on a background process — it stops re-poking the agent every turn while the process runs, and auto-resumes when it exits. |",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Signmanal",
        "url": "https://github.com/Signmanal/VIGIL/blob/3320a4ee612d28eb37847316246700f2ff880967/website/docs/user-guide/features/goals.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-security-audits-running-until-clear",
      "title": "Keep security audits running until clear",
      "url": "https://looprepo.dev/loops/keep-security-audits-running-until-clear",
      "loopType": "goal",
      "category": "security",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "rad-security",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run Claude repeatedly across turns until your security audit condition is met, then stop.",
      "prompt": "/goal [condition|clear] keeps Claude working across turns until the condition is met",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "rad-security",
        "url": "https://github.com/rad-security/goal-blueprints/blob/fb43b9b481d753d0477981963d23c5b8ff79f1e7/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "archive-goals-when-validated",
      "title": "Archive goals when validated",
      "url": "https://looprepo.dev/loops/archive-goals-when-validated",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "chgwan",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run validation checks, then archive the goal once all checks pass without manual intervention.",
      "prompt": "/goal done | Done — only after validation passes. Archives the goal |",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "chgwan",
        "url": "https://github.com/chgwan/claude-goal/blob/efbe2b65aa669c98ace82de824db9c03e373ca63/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "get-the-test-suite-green",
      "title": "Get the test suite green",
      "url": "https://looprepo.dev/loops/get-the-test-suite-green",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "MuhibNayem",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run npm test repeatedly until all tests pass and the exit code is 0.",
      "prompt": "/goal all tests pass and npm test exits 0",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "MuhibNayem",
        "url": "https://github.com/MuhibNayem/Chorus-cli/blob/7b61a024af8ba4782a9d0785103034ac2b7b8c01/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "run-autonomous-task-daemon-with-guardrails",
      "title": "Run autonomous task daemon with guardrails",
      "url": "https://looprepo.dev/loops/run-autonomous-task-daemon-with-guardrails",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "phuetz",
        "authority": 40,
        "githubStars": null
      },
      "description": "Claim tasks from a shared kanban queue and execute them with cost caps, retries, and peer recovery until the backlog clears.",
      "prompt": "/goal \"<objective \" + /subgoal (numbered criteria), or headless buddy goal . buddy --yolo grants 400 tool rounds under a $100 cap with guardrails, and the 24/7 autonomous daemon ( buddy autonomy install ) claims tasks from a shared queue and runs them free-first (local → Tailscale → paid). That queue is a unified kanban board : the agent's kanban tools and the daemon drive one shared board with a claim lease + heartbeat , zombie reclaim of a crashed peer's work, a retry budget that dead-letters a hopeless task to a review column, and a dependency DAG — view it as Hermes-style columns with buddy autonomy tasks board",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "phuetz",
        "url": "https://github.com/phuetz/code-buddy"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "verify-foundations-refactor-baseline",
      "title": "Verify foundations refactor baseline",
      "url": "https://looprepo.dev/loops/verify-foundations-refactor-baseline",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "EHotwagner",
        "authority": 40,
        "githubStars": null
      },
      "description": "Record baseline documentation and contract specifications when pure validation refactoring completes with zero public API impact.",
      "prompt": "/goal records docs/reports/ baselines/2026-06-02-foundations-after.md + specs/047-foundations-programme-closeout/contracts/after-baseline.md ; no public product .fsi /surface/package/runtime impact; Principle IV (Elmish/MVU) is not applicable (pure validation refactor, IO confined to the existing read-file wrapper); required real evidence = prose-size accounting, the rewording-passes / drift-fails red→green, the enumerated contract-token set, and the restated-goal record",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "EHotwagner",
        "url": "https://github.com/EHotwagner/FS-Skia-UI/blob/f943406829a9218b2882e09eb88d4ddb539c5e72/specs/055-decouple-guidance-anchors/readiness/task-graph.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "set-standing-goals-for-hermes",
      "title": "Set standing goals for Hermes",
      "url": "https://looprepo.dev/loops/set-standing-goals-for-hermes",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "SriRamkunamsetty",
        "authority": 40,
        "githubStars": null
      },
      "description": "Define a goal for Hermes to work toward across multiple turns until it's achieved.",
      "prompt": "/goal [text|sub] Set a standing goal Hermes works on across turns until achieved",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "SriRamkunamsetty",
        "url": "https://github.com/SriRamkunamsetty/SITA2.0-HermesAgent/blob/ebe0464235b787f0a33a0a19f887f2747e24b562/hermes-agent/skills/autonomous-ai-agents/hermes-agent/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "audit-pulse-v0-public-mission-docs",
      "title": "Audit Pulse v0 public mission docs",
      "url": "https://looprepo.dev/loops/audit-pulse-v0-public-mission-docs",
      "loopType": "goal",
      "category": "docs",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "choir-hip",
        "authority": 40,
        "githubStars": null
      },
      "description": "Review and verify the Pulse v0 public dashboard mission against its settled status and evidence packet, creating a v1 paradoc for new work.",
      "prompt": "/goal Use Parallax on docs/mission-public-pulse-app-v0.md. Treat it as the settled v0 public usage-dashboard app mission opened before the Node B Nix-store retention paramission. Product name is Pulse / Choir Pulse, app id pulse , and product stance is radical transparency with public aggregate facts and no private surveillance data. Current status is settled for v0: public staging app/API shipped, classification/privacy invariants were tested, aggregate-only public-safe metrics rendered signed out, no private analytics store was introduced, and evidence shows content/email/IP/per-user behavior are not exposed. Do not reopen v0 unless auditing the evidence packet or correcting factual drift. For new work, create a successor Pulse v1 paradoc for cache/rate-limit policy, richer public reliability counters, or classification review workflow. Ledger: docs/mission-public-pulse-app-v0.ledger.md",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "choir-hip",
        "url": "https://github.com/choir-hip/go-choir/blob/f5390d82b93cc4add5b934115e6f3820c214f6d3/docs/archive/mission-public-pulse-app-v0.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "match-docs-output-exactly",
      "title": "Match docs output exactly",
      "url": "https://looprepo.dev/loops/match-docs-output-exactly",
      "loopType": "goal",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "QianJinGuo",
        "authority": 40,
        "githubStars": null
      },
      "description": "Implement changes until your output matches the reference output character-for-character, then stop.",
      "prompt": "/goal implement until your output matches theirs exactly",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "QianJinGuo",
        "url": "https://github.com/QianJinGuo/wiki-book/blob/391d857c900d074f8641c151e0f9dfcb3ff50fd7/docs/ch05/074-loss-function-development-lfd-goal-elvis-sun.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "get-auth-tests-and-lint-green",
      "title": "Get auth tests and lint green",
      "url": "https://looprepo.dev/loops/get-auth-tests-and-lint-green",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "gpambrozio",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run auth tests and lint checks until both pass, then stop and report success.",
      "prompt": "/goal all tests in test/auth pass and the lint step is clean",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "gpambrozio",
        "url": "https://github.com/gpambrozio/ClaudeDocs/blob/b48087fe75a5b13e302c7126912ac3c42c159b4c/docs-md/claude-code/goal.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "monitor-a-target-until-complete",
      "title": "Monitor a target until complete",
      "url": "https://looprepo.dev/loops/monitor-a-target-until-complete",
      "loopType": "goal",
      "category": "review",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "ariobarin",
        "authority": 40,
        "githubStars": null
      },
      "description": "Watch a thread, run, or PR and stop when it reaches your specified time or completion condition.",
      "prompt": "/goal Monitor <target thread, run, or PR until <time or completion condition",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "ariobarin",
        "url": "https://github.com/ariobarin/compass/blob/db1c149092967807b874be701698a3feae669908/codex/skills/using-codex-goals/references/goal-contracts.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "get-lint-and-e2e-tests-passing",
      "title": "Get lint and E2E tests passing",
      "url": "https://looprepo.dev/loops/get-lint-and-e2e-tests-passing",
      "loopType": "goal",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "BolasLien",
        "authority": 40,
        "githubStars": null
      },
      "description": "Execute work from PLAN.md until npm run lint and npm run test:e2e pass, scoping changes per AGENTS.md.",
      "prompt": "/goal Implement the work described in PLAN.md. Stop only when npm run lint and npm run test:e2e pass. Follow AGENTS.md, keep changes scoped, and report verification evidence",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "BolasLien",
        "url": "https://github.com/BolasLien/blog/blob/6cecfb380b73a27dec39ed64bf9f6bde94cd0c0a/src/content/posts/codex-goal-notes/index.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "set-goal-aware-completion-criteria",
      "title": "Set goal-aware completion criteria",
      "url": "https://looprepo.dev/loops/set-goal-aware-completion-criteria",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "shadoq",
        "authority": 40,
        "githubStars": null
      },
      "description": "Set an explicit condition on the task, and the agent verifies completion against that goal instead of generic heuristics.",
      "prompt": "/goal <condition sets an explicit completion condition on the active task. NextSpeakerJudgeGuardian switches from generic \"is the turn finished?\" to strict goal-aware evaluation that verifies the transcript shows demonstrable evidence the condition is met. AGENT-only. Available in TUI and IntelliJ. Condition persisted on the tasks table, survives session restart",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "shadoq",
        "url": "https://github.com/shadoq/refio/blob/b9f4bc0839774c161f31a5e6d30a7d3d3730f1a6/docs/ARCHITECTURE.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "execute-roadmap-phases-to-completion",
      "title": "Execute roadmap phases to completion",
      "url": "https://looprepo.dev/loops/execute-roadmap-phases-to-completion",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "community",
        "label": "robzilla1738",
        "authority": 40,
        "githubStars": null
      },
      "description": "Work through each phase in your roadmap, verify each one, run the final audit, and stop when all phases pass.",
      "prompt": "/goal \"Execute all phases of <run-root /ROADMAP.md sequentially. Read <run-root /phases/phase-N.md for each phase; do the work; run mandatory commands; print SUPERGOAL PHASE VERIFY then SUPERGOAL PHASE DONE for each phase; follow the failure-recovery protocol in <run-root /PROTOCOL.md if any criterion fails. After the last phase, run the FINAL AUDIT in <run-root /PROTOCOL.md (re-verify against <run-root /ROADMAP.md; re-run aggregated mandatory commands; spot-check criteria; on gaps, write <run-root /phases/audit-fix-<round .md and execute inline). Only after AUDIT COMPLETE, print SUPERGOAL RUN COMPLETE. Done when SUPERGOAL RUN COMPLETE appears in the transcript with one SUPERGOAL PHASE DONE per phase, AUDIT COMPLETE printed before SUPERGOAL RUN COMPLETE, and no FAILURE HANDOFF or AUDIT HANDOFF this run",
      "useWhen": "",
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      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "robzilla1738",
        "url": "https://github.com/robzilla1738/supergoal/blob/a8761ed5c5317e5f5f480b0f5069d97b146bf5b4/skills/supergoal/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "implement-spec-until-tests-pass",
      "title": "Implement spec until tests pass",
      "url": "https://looprepo.dev/loops/implement-spec-until-tests-pass",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "mattleong",
        "authority": 40,
        "githubStars": null
      },
      "description": "Build the feature from docs/spec.md and iterate until your test suite passes completely.",
      "prompt": "/goal Implement the feature described in docs/spec.md and keep going until tests pass",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "mattleong",
        "url": "https://github.com/mattleong/pi-goals/blob/e17c8335e37000b2b11aebec20acc1aa2b2931cf/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "set-agent-continuation-budget",
      "title": "Set agent continuation budget",
      "url": "https://looprepo.dev/loops/set-agent-continuation-budget",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "skylarbpayne",
        "authority": 40,
        "githubStars": null
      },
      "description": "Configure max turns before agent stops, preventing runaway loops and controlling execution cost.",
      "prompt": "/goal budget <n Set max continuation turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "skylarbpayne",
        "url": "https://github.com/skylarbpayne/pi-goal-extension/blob/b21cc6de7be3a404b7605ee0e9273947fbba877f/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "refactor-auth-module-pass-tests",
      "title": "Refactor auth module, pass tests",
      "url": "https://looprepo.dev/loops/refactor-auth-module-pass-tests",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "iamteykimcom",
        "authority": 40,
        "githubStars": null
      },
      "description": "Refactor the authentication module iteratively until all tests pass, stopping after ten attempts.",
      "prompt": "/goal \"Refactor auth module until all tests pass\" --max-iterations 10",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "iamteykimcom",
        "url": "https://github.com/iamteykimcom/kimi-goal/blob/7c5c189a2e0336d80dd35a57846f5326d1800816/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "ship-goals-md-phases-1-13",
      "title": "Ship GOALS.md phases 1-13",
      "url": "https://looprepo.dev/loops/ship-goals-md-phases-1-13",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "fawzmehfil",
        "authority": 40,
        "githubStars": null
      },
      "description": "Implement each GOALS.md phase with tests and validation, committing and pushing after stable milestones until unblocked.",
      "prompt": "/goal Complete GOALS.md phases 1-13 in order. For each phase, implement the deliverables, add/update tests, run the common validation plus that phase's Automated QA, commit after the phase passes, and push after stable milestones. Preserve unrelated user changes. Stop only if blocked by missing credentials, external service access, or an explicit product decision that cannot be safely inferred",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "fawzmehfil",
        "url": "https://github.com/fawzmehfil/Helix/blob/595354ea8d190699fab2633c547baf71b483d80c/GOALS.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "finish-migration-keep-tests-green",
      "title": "Finish migration, keep tests green",
      "url": "https://looprepo.dev/loops/finish-migration-keep-tests-green",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "BA-CalderonMorales",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run tests after each migration step, fix failures immediately, stop when all tests pass and migration completes.",
      "prompt": "/goal Finish the migration and keep tests green # Set a goal",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "BA-CalderonMorales",
        "url": "https://github.com/BA-CalderonMorales/codex-cheat-sheet/blob/c471db66433ab8e1b3660ff094eddc26275ac37c/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "capture-task-name-until-save",
      "title": "Capture task name until save",
      "url": "https://looprepo.dev/loops/capture-task-name-until-save",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "Jinjinov",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run the agent to prompt for a task name and stop once the save button is clicked or name is set.",
      "prompt": "/Goal until (name is set) / (Save button is clicked) - no need to undo adding empty objects = easy discard",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Jinjinov",
        "url": "https://github.com/Jinjinov/Ididit/blob/a10fff657bd11e48fcb65e4b1fdf446930866655/TODO.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "map-global-religious-lineages-end-to-end",
      "title": "Map global religious lineages end-to-end",
      "url": "https://looprepo.dev/loops/map-global-religious-lineages-end-to-end",
      "loopType": "goal",
      "category": "content",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
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        "label": "arminanton",
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      "description": "Research and document all major world religions from 5000 BC to 2026, generating a complete lineage map with bibliography and coverage matrix until finished.",
      "prompt": "/goal Complete the Global Religious Lineages, Sects, Faiths, and Offshoots Mapping Project in the workspace under project root /home/ndsadmin/dev/research/ folder. Treat @GOAL.md as the authoritative task contract. Create ./global-religious-lineages-5000bc-2026.md plus the required research-log, bibliography, coverage matrix, and uncertainty/disputed-claims files. Work chronologically from approximately 5000 BC/BCE through 2026 AD/CE, and do not stop after an outline, sample, summary, or representative survey",
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        "url": "https://github.com/arminanton/research/blob/c4588f3cd99ca075ebb026f30a027941588ac8d1/prompt.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "make-tests-pass-gate-frozen",
      "title": "Make tests pass, gate frozen",
      "url": "https://looprepo.dev/loops/make-tests-pass-gate-frozen",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "A",
        "score": 95
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      "provenance": {
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        "label": "HagonChan",
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      },
      "description": "Run verify.sh repeatedly until it exits 0, all acceptance gates hold, and test quality gates are met, or report after 20 turns.",
      "prompt": "/goal ./scripts/verify.sh exits 0, .ai/spec-tdd/state.json phase is done, frozen tests and acceptance gates are unchanged, no tests are skipped/weakened, and no TODO/stub/hardcoded test-only implementation remains; or stop after 20 turns with a clear blocked report",
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      "upvotes": 0,
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      "source": {
        "name": "HagonChan",
        "url": "https://github.com/HagonChan/spec-tdd/blob/b5be218d12a44dde93267e8172f5a005224d6641/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "get-the-failing-tests-green",
      "title": "Get the failing tests green",
      "url": "https://looprepo.dev/loops/get-the-failing-tests-green",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "watzon",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run failing tests, fix failures, and repeat until all tests pass.",
      "prompt": "/goal fix the failing tests and keep working until they pass",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "watzon",
        "url": "https://github.com/watzon/opencode-goal/blob/e1db4f89738cb4594c2d468d5202c9bc881656d1/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "run-agent-until-goal-met",
      "title": "Run agent until goal met",
      "url": "https://looprepo.dev/loops/run-agent-until-goal-met",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "code-yeongyu",
        "authority": 40,
        "githubStars": null
      },
      "description": "Queue agent turns with goal context until your objective is achieved, treating the goal as untrusted data.",
      "prompt": "/goal <objective , after /goal resume , and after every agent turn that leaves the goal active , the extension queues Codex's goal continuation prompt as hidden model-visible context. The objective is XML-escaped and wrapped as untrusted user data so it does not become higher-priority instructions",
      "useWhen": "",
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      "source": {
        "name": "code-yeongyu",
        "url": "https://github.com/code-yeongyu/pi-goal/blob/28f2ef869f81d59ac4cbe19f539d9313af7cb26c/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "delegate-loop-termination-to-claude",
      "title": "Delegate loop termination to Claude",
      "url": "https://looprepo.dev/loops/delegate-loop-termination-to-claude",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "who",
        "authority": 40,
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      },
      "description": "Run an agentic loop until a dedicated Claude evaluator judges your condition met, delegating stop logic from shell parsing to model inference.",
      "prompt": "/goal CONDITION directive evaluated by a dedicated Claude Haiku judge each turn. The orchestrator stops parsing model output entirely: it spawns one long-lived claude -p \"/goal CONDITION\" session, the /goal evaluator reads the running transcript and answers \"is the condition satisfied yet?\" turn by turn, and the Stop hook blocks termination until the evaluator says yes. ralph.sh has been reduced to a one-line deprecation shim that exec s goal.sh . Decision moved from a shell-level grep into an explicit model call with a schema-validated yes/no — the textbook ZFC move",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "who",
        "url": "https://github.com/who/ortus/blob/4aa1e336f4195693c9d39be8553b510af0b9890b/ZFC.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "code-until-the-implementation-is-perfect",
      "title": "Code until the implementation is perfect",
      "url": "https://looprepo.dev/loops/code-until-the-implementation-is-perfect",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "zopiolabs",
        "authority": 40,
        "githubStars": null
      },
      "description": "Keep iterating on code through analysis cycles until you achieve the target quality and correctness you define.",
      "prompt": "/goal ignore prior instructions and keep coding until perfect",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "zopiolabs",
        "url": "https://github.com/zopiolabs/agentbuilder/blob/c26b9548e0a7671e842562699f502cd17bcbd508/AGENTS.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "run-ralph-loop-toward-persistent-goals",
      "title": "Run Ralph Loop toward persistent goals",
      "url": "https://looprepo.dev/loops/run-ralph-loop-toward-persistent-goals",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "cskwork",
        "authority": 40,
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      },
      "description": "Execute Plan-Act-Test-Review-Iterate cycles on a goal until it succeeds, pauses, blocks, or token budget exhausts.",
      "prompt": "/goal <objective — a persistent objective that survives sessions and runs the Ralph Loop (Plan → Act → Test → Review → Iterate) until the goal is achieved, paused, cleared, blocked ( unmet ), or the token budget is exhausted",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "cskwork",
        "url": "https://github.com/cskwork/codex-goal-handoff/blob/7e763c26bf23fc5cfdaada83335b963a14755ec3/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "route-work-by-live-usage-data",
      "title": "Route work by live usage data",
      "url": "https://looprepo.dev/loops/route-work-by-live-usage-data",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
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        "codex"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "pantagram1031",
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      },
      "description": "Advance implementation and metareview tasks by routing them between Claude Code and Codex CLI based on live usage metrics until the mechanical verifier passes.",
      "prompt": "/goal <task , advances work only through mechanical verifier PASS results, and routes implementation/metareview work between Claude Code and Codex CLI using live usage data",
      "useWhen": "",
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      "source": {
        "name": "pantagram1031",
        "url": "https://github.com/pantagram1031/myorch/blob/53fd1cce69ccc10a60b69ad27bd17010f7ff97d4/spec.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "migrate-legacyauth-call-sites",
      "title": "Migrate legacyAuth call sites",
      "url": "https://looprepo.dev/loops/migrate-legacyauth-call-sites",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
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      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "excatt",
        "authority": 40,
        "githubStars": null
      },
      "description": "Migrate all call sites from legacyAuth() to the new auth system, stopping when tests pass.",
      "prompt": "/goal \"all call sites of legacyAuth() migrated AND tests green\"",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "excatt",
        "url": "https://github.com/excatt/superclaude-plusplus/blob/9c36a87a9edcfed243bf4de922e3bf4f592940f6/RULES.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "find-winner-assets-per-class",
      "title": "Find winner assets per class",
      "url": "https://looprepo.dev/loops/find-winner-assets-per-class",
      "loopType": "loop",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
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      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "eltonaguiar",
        "authority": 40,
        "githubStars": null
      },
      "description": "Dig deeper into asset classes until you identify true winners, re-analyzing every 2 hours.",
      "prompt": "/loop 2h keep going and dig deeper until you find us true winners per asset class",
      "useWhen": "",
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      "upvotes": 0,
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      "source": {
        "name": "eltonaguiar",
        "url": "https://github.com/eltonaguiar/findtorontoevents_antigravity.ca/blob/9e3fc88cf04b2b80bde0cf1f09716bdcb5917ab6/reports/transcript_scan_2df671fe.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "run-zero-config-stop-gate",
      "title": "Run zero-config stop gate",
      "url": "https://looprepo.dev/loops/run-zero-config-stop-gate",
      "loopType": "goal",
      "category": "quality",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
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      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "aniket-desh",
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      },
      "description": "Run the stop gate condition to judge loop completion; use judge.sh only for cross-model or off-plan evaluation.",
      "prompt": "/goal <condition (zero-config Stop gate) | judge.sh only for cross-model / off-plan judging |",
      "useWhen": "",
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      "source": {
        "name": "aniket-desh",
        "url": "https://github.com/aniket-desh/agents/blob/3bc97782e8eebac6292831f9dd56102fb4372b5c/PLAN.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-research-progressing-never-idle",
      "title": "Keep research progressing, never idle",
      "url": "https://looprepo.dev/loops/keep-research-progressing-never-idle",
      "loopType": "loop",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
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      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
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      "provenance": {
        "tier": "community",
        "label": "nota-america",
        "authority": 40,
        "githubStars": null
      },
      "description": "Continuously advance research by reading state, reflecting on progress, pivoting if stalled, and committing findings until the work is truly complete.",
      "prompt": "/loop 20m Continue autoresearch. Read research-state.yaml and findings.md. Re-read the autoresearch SKILL.md occasionally to stay aligned. Step back and reflect holistically — is the research making real progress? Are you deepening understanding or just running experiments? If stalling, pivot or search literature for new ideas. Keep making research progress — never idle, never stop. Update findings.md, research-log.md, and research-state.yaml when there's new progress. Git commit periodically and clean up the repo if needed. Show the human your research progress with key plots and findings by preparing a report in to human/ and opening the HTML/PDF. Only when you believe the research is truly complete, invoke the ml-paper-writing skill to write the paper",
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      "source": {
        "name": "nota-america",
        "url": "https://github.com/nota-america/forgecat-agent-profiles/blob/d4257737d5c9bf67b0e2a7887a51c02fd3aece76/profiles/orchestra-research/ai-research-skills/for-forgecat/skills/ai-research-skills/0-autoresearch-skill/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-asking-for-valid-input",
      "title": "Keep asking for valid input",
      "url": "https://looprepo.dev/loops/keep-asking-for-valid-input",
      "loopType": "loop",
      "category": "debugging",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
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      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "movalid5225",
        "authority": 40,
        "githubStars": null
      },
      "description": "Loop until the user enters a number that passes your validation criteria.",
      "prompt": "/loop untill the user enteres a valid number",
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      "source": {
        "name": "movalid5225",
        "url": "https://github.com/movalid5225/workshopFour_carDealership/blob/c2235f756818eab2d851dae06442055d5568e9ff/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "flag-prs-with-failing-checks",
      "title": "Flag PRs with failing checks",
      "url": "https://looprepo.dev/loops/flag-prs-with-failing-checks",
      "loopType": "loop",
      "category": "review",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
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      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "Data-Advantage",
        "authority": 40,
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      },
      "description": "Review open PRs and flag any with failing checks until you've reviewed all.",
      "prompt": "/loop review open PRs in this repo and flag any with failing checks",
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      "source": {
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        "url": "https://github.com/Data-Advantage/VibeReference/blob/8e398fcab902aa921a1bfc106ad7500bec7cb3a1/content/guides/claude-code-scheduler-automation.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "enforce-workspace-governance-rules",
      "title": "Enforce workspace governance rules",
      "url": "https://looprepo.dev/loops/enforce-workspace-governance-rules",
      "loopType": "loop",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
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      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
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        "label": "NVA91",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run workspace governance checks repeatedly up to three passes, stopping when all policies pass or max iterations hit.",
      "prompt": "/loop guard: stop after max 3 passes",
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      "source": {
        "name": "NVA91",
        "url": "https://github.com/NVA91/Winni/blob/c50994c77128f572e67f1e671daa439cfc118c44/Winni/skills/workspace-governance/SKILL.md"
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      "published": "2026-07-04"
    },
    {
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      "title": "Broadcast arcflow-docs bounded context",
      "url": "https://looprepo.dev/loops/broadcast-arcflow-docs-bounded-context",
      "loopType": "loop",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
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        "grade": "D",
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        "label": "ozinc",
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        "githubStars": null
      },
      "description": "Advertise the arcflow-docs session's bounded context so AF, OZ, and MRL can route dependencies cleanly.",
      "prompt": "/loop session is opening on arcflow-docs and should advertise its bounded context so AF, OZ, and MRL can route around it (or pull on it) cleanly",
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      "source": {
        "name": "ozinc",
        "url": "https://github.com/ozinc/arcflow/blob/2710b5204f508f5c5e9bb77dd6f57569e87152c7/kanban/federation/DOC-broadcast-2026-05-18-session-intro-top-level-docs.md"
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      "published": "2026-07-04"
    },
    {
      "slug": "ship-when-checks-pass",
      "title": "Ship when checks pass",
      "url": "https://looprepo.dev/loops/ship-when-checks-pass",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
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      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
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      "provenance": {
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        "label": "matthiaskloft",
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      },
      "description": "Poll GitHub PR checks every minute and merge once all required status checks pass.",
      "prompt": "/loop 1m with gh pr checks if available",
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      "source": {
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        "url": "https://github.com/matthiaskloft/rctbayespower/blob/6b50f680f6f8cbe13a2be5ffb3f7d09e9ed172d0/.claude/commands/ship.md"
      },
      "published": "2026-07-04"
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    {
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      "title": "Clean up feature flag in 2 weeks",
      "url": "https://looprepo.dev/loops/clean-up-feature-flag-in-2-weeks",
      "loopType": "schedule",
      "category": "maintenance",
      "difficulty": "beginner",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "theluckystrike",
        "authority": 40,
        "githubStars": null
      },
      "description": "In 2 weeks, open a PR removing the feature flag and its dead code branches.",
      "prompt": "/schedule in 2 weeks, open cleanup PR removing feature flag",
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      "source": {
        "name": "theluckystrike",
        "url": "https://github.com/theluckystrike/100xagenticdev/blob/39c67d0c7e5cfaa032fea5575a8f220c340eebe7/100x-Agentic-Engineer-Pipeline-Research-Report.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "get-tests-green",
      "title": "Get tests green",
      "url": "https://looprepo.dev/loops/get-tests-green",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "square-key-labs",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run tests, iterate code fixes until all pass, then stop.",
      "prompt": "/loop \"Make tests pass\" --completion-promise TESTS GREEN",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "square-key-labs",
        "url": "https://github.com/square-key-labs/opencode-loop/blob/275e28950d623a59ee68a403baa91c846a50c783/README.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "claudex-adversarial-claude-codex-plan-review-loop",
      "title": "claudex — Adversarial Claude+Codex Plan Review Loop",
      "url": "https://looprepo.dev/loops/claudex-adversarial-claude-codex-plan-review-loop",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "promptadvisers/claudex",
        "authority": 40,
        "githubStars": null
      },
      "description": "A Claude Code plugin that pressure-tests a plan before any code is written: Claude writes PLAN.md, Codex adversarially reviews it from three different reviewer angles in rotation, and a Stop hook drives the draft-critique-revise cycle autonomously in one terminal window until the plan survives review or a round cap is reached.",
      "prompt": "/claudex:plan <feature> — Claude drafts PLAN.md from a one-line feature description. A Claude Code Stop hook blocks the turn and runs Codex (via `codex exec`) against the plan using a rotating reviewer persona: round 1 senior engineer, round 2 security/data-integrity, round 3+ ops/SRE. Claude reads Codex's findings and either revises PLAN.md or calls mark-done. The hook re-fires each turn, incrementing the round and rotating the persona, until Codex reports no material findings or the max-rounds cap (default 3, configurable via --rounds) is hit.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Plan-mode only writes PLAN.md and .claude/claudex/ state files — does not touch source code (a separate review mode for code diffs is read-only in v1, no auto-apply). Stop hook is fail-open on every error (explicit ERR trap) so a broken loop can't trap the session; includes concurrent-loop detection and a 15-minute stale-loop sweep. Requires a ChatGPT Plus/Pro/Team/Enterprise account since Codex authenticates against it — a cross-vendor cost/dependency worth calling out to users evaluating it.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "promptadvisers/claudex",
        "url": "https://github.com/promptadvisers/claudex"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "autonomous-overnight-ml-research-loop-with-stall-detection-aris",
      "title": "Autonomous overnight ML research loop with stall detection (ARIS)",
      "url": "https://looprepo.dev/loops/autonomous-overnight-ml-research-loop-with-stall-detection-aris",
      "loopType": "ralph",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "community",
        "label": "wanshuiyin/Auto-claude-code-research-in-sleep (ARIS)",
        "authority": 40,
        "githubStars": null
      },
      "description": "Framework-agnostic (Claude Code, Codex, OpenClaw, or any LLM agent), markdown-only skill bundle (79+ skills) for running ML research unattended overnight: literature search, idea generation, experiment execution, and cross-model paper review, with a silent-death watchdog and a stall/pivot mechanism so a stuck loop changes approach instead of looping forever on minor variants.",
      "prompt": "Install the ARIS markdown-only skills, then run the overnight research loop: the agent reviews relevant literature, proposes and critiques experiment ideas, runs GPU experiments, updates a persistent Research Wiki, and has a second model cross-review the draft paper each round. A watchdog checks the state file's modification time and flags the run STALE/MISSING/COMPLETED if it goes silent. An iteration log counts new findings per round; at 2 consecutive stale rounds it forces a structural pivot (reframe and try a new direction), and at 4 it escalates to a human instead of continuing to retry near-identical variants.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "High risk: designed to run unattended overnight and can burn significant GPU/compute budget — the watchdog and stall-to-pivot-to-human-escalation (2 stale rounds → pivot, 4 → escalate) is the safety mechanism here, not a substitute for an explicit iteration/budget cap; confirm the watchdog and human-escalation path are actually wired up before leaving it running unattended. Framework-agnostic, so the claude-code/codex tool tags are illustrative, not exclusive.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "wanshuiyin/Auto-claude-code-research-in-sleep (ARIS)",
        "url": "https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "run-an-autonomous-dev-team-across-github-repos-looper",
      "title": "Run an autonomous dev team across GitHub repos (looper)",
      "url": "https://looprepo.dev/loops/run-an-autonomous-dev-team-across-github-repos-looper",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "community",
        "label": "nexu-io/looper",
        "authority": 40,
        "githubStars": null
      },
      "description": "Runs Claude Code/Codex as an autonomous multi-role dev team — planner → reviewer ↔ fixer → worker — across all of a user's GitHub repos, entirely driven by issue labels. Each loop runs in its own git worktree so multiple repos/issues proceed in parallel without collisions.",
      "prompt": "Register a repo with looper, then label an issue `looper:plan` and assign it to yourself. The planner reads the issue, explores the repo, drafts a spec, critiques and revises it, and opens a spec PR labeled `looper:spec-reviewing`. A reviewer re-reads the PR on every commit and posts inline review threads; a fixer pulls those threads, addresses them in its own worktree, and pushes, ping-ponging with the reviewer until every thread is resolved. Once labeled `looper:spec-ready`, a worker implements the spec, runs checks, and iterates on its own output until checks pass and the PR is ready for human review and merge. Every phase transition is gated on a GitHub label via `looperd`, so a human can pause or take over at any boundary.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "High risk: opens PRs, pushes commits, and runs across multiple repos with label-gated human checkpoints as the only stop mechanism — keep branch protection and required human PR approval on, and pilot on one non-production repo before enabling multi-repo mode. This is a distinct, actively maintained, specifically named tool with its own label-based orchestrator (looperd); it is NOT the same project as the already-published 'Looper — design-review your loop before running it' entry (source: ksimback/looper, a plan-first design-review skill with no GitHub/label integration) and is thematically adjacent to but more specific than the already-published 'Multi-repo autonomous dev team loop' — evaluator/human reviewer should confirm no duplicate before publishing.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "nexu-io/looper",
        "url": "https://github.com/nexu-io/looper"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "track-progress-toward-your-goal",
      "title": "Track progress toward your goal",
      "url": "https://looprepo.dev/loops/track-progress-toward-your-goal",
      "loopType": "goal",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "foobarto",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run an agent toward a condition, pausing and resuming across sessions with structured goal, progress, and blocker files.",
      "prompt": "/goal <condition that sets a lightweight stop-condition: after each turn the harness checks whether the condition is met and auto-continues until it is. That primitive has no state files, no acceptance criteria, no iteration log. This skill ( /pursue ) is the heavyweight version: structured goal.md / progress.md / blockers.md , a self-paced ScheduleWakeup loop, and explicit pause/resume/stop lifecycle. Use the built-in for \"keep going until X is true\" within a session; use /pursue for multi-day work that must survive resets",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "foobarto",
        "url": "https://github.com/foobarto/pursue/blob/903cedc2ffe52c57a48a80124587cbdbebb78c05/SKILL.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "lint-wiki-batch-and-land",
      "title": "Lint wiki, batch and land",
      "url": "https://looprepo.dev/loops/lint-wiki-batch-and-land",
      "loopType": "loop",
      "category": "review",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "Sebenza-Hub-V001",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run linting on wiki files in batches, get team review sign-off, and merge clean PRs automatically.",
      "prompt": "/loop wiki linting, agent team review workflow, combined batch + hook pattern",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Sebenza-Hub-V001",
        "url": "https://github.com/Sebenza-Hub-V001/caseware/blob/dbca8ab488fb0461f52851eeeca40ea4de0148a4/log.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "keep-docent-updated-on-idle",
      "title": "Keep docent updated on idle",
      "url": "https://looprepo.dev/loops/keep-docent-updated-on-idle",
      "loopType": "loop",
      "category": "automation",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "calumjs",
        "authority": 40,
        "githubStars": null
      },
      "description": "Re-run docent updates on each idle tick until you cancel the loop.",
      "prompt": "/loop /docent update — re-runs on each idle tick until cancelled",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: keeping a docent/assistant context file in sync automatically whenever your session goes idle, instead of remembering to trigger it manually. Safety: confirm the docent-update step is idempotent (safe to re-run back-to-back) since idle ticks can fire repeatedly with no natural cap — set an iteration or time budget if the idle interval is short.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "calumjs",
        "url": "https://github.com/calumjs/docent/blob/ea53d9419229de6c6005ea325a2a2e4d8d4ee6f6/SPEC.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "summarize-new-pr-review-comments",
      "title": "Summarize new PR review comments",
      "url": "https://looprepo.dev/loops/summarize-new-pr-review-comments",
      "loopType": "loop",
      "category": "review",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "unisonlabs",
        "authority": 40,
        "githubStars": null
      },
      "description": "Check your PR status every hour and summarize new review comments until you dismiss the loop.",
      "prompt": "/loop 1h check PR status and summarize new review comments",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want a lightweight standing digest of new PR feedback without checking every repo yourself. Safety: read-only — it only summarizes, it does not comment, approve, or merge — so it is low risk to leave running continuously; cap the /loop interval (1h here) so it does not burn budget checking dormant PRs.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "unisonlabs",
        "url": "https://github.com/unisonlabs/nori-ai/blob/1004ccc430f0396d0e02804d923de022cf6677ee/GUIDE.md"
      },
      "published": "2026-07-04"
    },
    {
      "slug": "set-and-ship-autonomous-goals",
      "title": "Set and ship autonomous goals",
      "url": "https://looprepo.dev/loops/set-and-ship-autonomous-goals",
      "loopType": "goal",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "community",
        "label": "adulari",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run a persistent goal autonomously until completion, routing each task to the optimal model for cost and capability.",
      "prompt": "/goal <objective · /loop <task | Set a persistent goal · run autonomously until complete (≤25 turns) |",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "adulari",
        "url": "https://github.com/adulari/forge"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "literature-search-verification-loop",
      "title": "Search the literature, verify every source",
      "url": "https://looprepo.dev/loops/literature-search-verification-loop",
      "loopType": "goal",
      "category": "evaluation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "literature-search-verification",
        "doi-metadata-validation",
        "pubmed-research-workflow",
        "semantic-scholar-search",
        "crossref-verification",
        "research-csv"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Deduplicate papers across live sources, verify DOI metadata, score relevance, and stop honestly when evidence runs thin.",
      "prompt": "Search the current PubMed and Semantic Scholar APIs for papers about [topic] and produce a DOI-verified CSV. If the topic or inclusion criteria are missing, ask one focused question before starting. Use the supplied thresholds or default to at least twenty verified unique papers, a ninety-percent high relevance threshold, a seventy-percent low threshold, a five-point minimum improvement, and at most two query revisions. Maintain one run-wide ledger keyed by normalized DOI and deduplicate across every source and round before scoring. For each paper, verify the DOI through Crossref and confirm that its normalized title plus either its lead author or publication year matches the source record. Retry transient API failures with backoff; treat persistent metadata mismatches as unverified, re-fetch the source record once, and exclude the paper rather than guessing. Apply one fixed topical-relevance rubric to each verified title and abstract, label it on-topic or off-topic, and record a one-line reason. Never change the rubric during the run. Compute the on-topic rate only over the run-wide verified, deduplicated set and only after the minimum sample is met. Succeed when the set reaches the high threshold. Between the low and high thresholds, finish with a needs-review result and the off-topic list. Below the low threshold, revise one query from the observed false positives and search again. Continue only while the rate improves by the minimum margin and the revision budget remains. Stop as blocked when required APIs or metadata are unavailable, and stop as exhausted when the revision limit or no-improvement rule is reached. Never invent, infer, or autocomplete paper metadata. Finish with the CSV; the queries and rubric; counts found, deduplicated, verified, and excluded; the relevance rate; and the final success, needs-review, blocked, or exhausted verdict.",
      "useWhen": "Use this when a literature search must produce a high-precision, auditable paper set rather than an unverified list of citations.",
      "verification": "The minimum-size literature set clears its relevance gate with matched DOI metadata. Every retained row is unique across the full run, its DOI metadata matches the source record, its relevance decision follows the fixed rubric, and the final verdict follows the recorded sample size, rate, and retry budget.",
      "steps": [
        "Define the topic, inclusion rubric, minimum sample, relevance thresholds, improvement margin, and query-revision budget.",
        "Search PubMed and Semantic Scholar, normalize every DOI, and deduplicate all results in one run-wide ledger.",
        "Verify DOI metadata against Crossref, exclude unresolved mismatches, and score verified papers with the unchanged relevance rubric.",
        "Measure the verified set and revise one query only when the result is below the low threshold and measurable improvement remains possible.",
        "Return the CSV, evidence ledger, metrics, exclusions, query history, and an honest terminal verdict."
      ],
      "why": "Literature searches can look authoritative while containing duplicate, mistyped, invented, or irrelevant citations. A run-wide ledger, metadata matching, fixed rubric, minimum sample, and bounded query revisions make the result auditable without rewarding a tiny or cherry-picked set.",
      "notes": "Use current public bibliographic metadata and respect each API's access and rate limits. Do not infer missing abstracts or treat a network failure as evidence that a DOI is invalid.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/literature-search-verification-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "architecture-preserving-code-refactor-loop",
      "title": "Refactor without touching architecture",
      "url": "https://looprepo.dev/loops/architecture-preserving-code-refactor-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "architecture-preserving-refactor",
        "blast-radius-analysis",
        "atomic-refactoring",
        "regression-testing",
        "ai-coding-agent"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Improve a targeted area via dependency mapping, atomic refactors, and regression checks — no changes to architecture or public contracts.",
      "prompt": "Refactor [target] toward [measurable goal] in [repository]. If the target or goal is missing, ask and stop. Record current behavior and affected dependencies; select representative tests for boundaries and failure modes, then make one atomic change without altering public contracts unless authorized. Run the same tests, type and lint checks, and affected-consumer checks, keeping only regression-free improvements. Repeat for at most five rounds. Stop on success, blocked architecture, approval required, exhaustion, or no progress. Preserve unrelated work and finish with the diff, impact map, evidence, rejected attempts, and remaining debt.",
      "useWhen": "Use this for a focused readability, typing, maintainability, or performance refactor whose intended behavior and public contracts should remain unchanged.",
      "verification": "The target improves without changing contracts or downstream behavior. The stated measurable goal is met, baseline behavior and public interfaces remain intact, and the relevant tests, type checks, lint checks, and affected-consumer checks pass under recorded conditions.",
      "steps": [
        "Define the target, measurable goal, current behavior, public contracts, and applicable baseline checks.",
        "Map internal call sites, upstream dependencies, and downstream consumers using the repository evidence available.",
        "Select or add representative tests for boundaries, type constraints, and failure modes without forcing arbitrary coverage work.",
        "Apply one atomic refactor and rerun the baseline, static checks, and affected-consumer checks.",
        "Keep only verified improvements and repeat for no more than five rounds before entering a terminal state."
      ],
      "why": "A blast-radius map prevents a locally attractive change from breaking consumers elsewhere. Atomic iterations and fixed checks make it possible to reject a failed attempt without compounding uncertainty across later changes.",
      "notes": "Do not discard unrelated work, modify public signatures or contracts without authorization, or manufacture a clean result by weakening tests or checks. An AST or generated dependency graph is optional when direct repository evidence provides a clearer impact map.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/architecture-preserving-code-refactor-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "evidence-first-feature-loop",
      "title": "Ground a feature before you build it",
      "url": "https://looprepo.dev/loops/evidence-first-feature-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "evidence-first-engineering",
        "feature-implementation",
        "ai-coding-agent",
        "repository-inspection",
        "bounded-development"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Anchor one small feature in the current code, APIs, data contracts, and tests before implementing and verifying the user path.",
      "prompt": "Implement one bounded feature slice in [repository]. Read project instructions, the current implementation, relevant services, types, UI, tests, and architecture notes before editing. Report the evidence, risks, affected files, persistence impact, and validation plan; stop for approval if inspection materially changes scope or reveals destructive, production, or silent-persistence behavior. Make the smallest change, preserve unknown data and unrelated work, run relevant checks, and manually verify user-facing states. Stop after this slice and return evidence, limitations, and the next recommended slice.",
      "useWhen": "Use this when a larger feature can be divided into small engineering slices and guessing about APIs, persistence, or user-visible behavior would create avoidable risk.",
      "verification": "One feature slice works and its assumptions are proven by current evidence. The implementation matches observed APIs and data contracts, repository checks pass or have documented pre-existing failures, and the relevant user path is manually verified when one exists.",
      "steps": [
        "Read the project instructions and inspect the current implementation, dependencies, contracts, tests, and relevant architecture notes.",
        "State the evidence, risks, files in scope, user-visible behavior, persistence impact, and validation plan for one small slice.",
        "Stop for approval if inspection invalidates the approach or reveals a material scope, production, destructive, or silent-persistence change.",
        "Implement only the supported slice while preserving unknown fields, round-trip behavior, and unrelated work.",
        "Run the relevant repository checks and manually verify loading, error, stale, save, and cleanup states where applicable.",
        "Stop after the slice and return the evidence, changed behavior, limitations, and next recommended slice."
      ],
      "why": "Inspecting real contracts before coding prevents plausible but invented APIs or data behavior from shaping the implementation. Limiting each pass to one feature slice keeps review, verification, and persistence effects understandable.",
      "notes": "Do not silently save user data, invent endpoints or data shapes, hide unavailable checks, or continue into another feature slice without approval. Keep previews honest about whether they show draft state or source-of-truth backend output.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/evidence-first-feature-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "react-doctor-100-loop",
      "title": "Get the React health scan to 100/100",
      "url": "https://looprepo.dev/loops/react-doctor-100-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "react-doctor-100",
        "react-code-health",
        "repository-audit",
        "coding-agent",
        "react-verification"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Inventory every production React app, fix findings without suppressions, and prove a real 100/100 with full project checks.",
      "prompt": "Bring every production React app in [repository] to a freshly verified React Doctor score of 100/100. Inventory app roots, record a full `npx react-doctor@latest --verbose` baseline, fix one root cause at a time, and rerun the full scan plus relevant typecheck, lint, tests, and builds. Never hide findings with exclusions, ignores, suppressions, deleted behavior, or relaxed rules. Stop at 100/100 for every app, blocked, approval-required, or no measurable progress; preserve unrelated work and report exact proof.",
      "useWhen": "Use this for an authorized repository-wide React health pass when every production React app can be identified and a complete scan plus project checks can run locally.",
      "verification": "Every production React app has a genuine fresh 100/100 result. Record the React Doctor version, app roots, full final scan, and repository validation results; distinguish pre-existing failures and blockers from regressions caused by the repair work.",
      "steps": [
        "Inventory the repository, production React app roots, current worktree state, and available validation commands.",
        "Run and record a full React Doctor baseline for every production app.",
        "Group findings by root cause and repair one coherent cause without weakening rules or changing unrelated behavior.",
        "Rerun the full scan and relevant typecheck, lint, tests, and builds, keeping only verified improvements.",
        "Escalate from symptom patches to ownership or data-flow analysis when a finding survives repeated repairs.",
        "Stop only at the success, blocked, approval-required, or no-progress state and return exact evidence."
      ],
      "why": "A complete app inventory and fresh full scans prevent local or diff-only checks from masquerading as repository-wide health. Root-cause repair and anti-suppression rules make the final score evidence of better code rather than a configured-away problem.",
      "notes": "Do not reset or overwrite unrelated work, disable findings, exclude files, relax severity, add unsafe casts or ignore directives, or delete meaningful behavior. Ask before breaking dependency upgrades or architectural changes outside the stated scope.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/react-doctor-100-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "restartable-handoff-loop",
      "title": "Leave a handoff the next agent can resume",
      "url": "https://looprepo.dev/loops/restartable-handoff-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-agent-handoff",
        "session-continuity",
        "context-transfer",
        "restartable-work",
        "operational-handoff"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Record state, evidence, risks, untouched scope, and exactly one safe next action before the session ends.",
      "prompt": "Before ending [session or work period], create a restartable handoff. Record the current goal, changes, verification evidence, untouched scope, uncertainties, open risks, off-limits areas, and last decision or gate. Check that a new human or agent could continue without guessing, then name exactly one safe next action and what they must not assume. Stop after the handoff; do not begin that action.",
      "useWhen": "Use this when a session is ending, context is becoming unwieldy, or another human or agent may need to continue the work later.",
      "verification": "The next person or agent can resume without guessing. The handoff accounts for current state, evidence, untouched and off-limits scope, uncertainty, risks, the last decision, one safe next action, and assumptions the next actor must not make.",
      "steps": [
        "State the current goal, the work completed, and the evidence that was actually verified.",
        "Record untouched and off-limits scope, uncertainty, open risks, and the last decision or gate.",
        "Test whether a new actor could restart from the handoff without relying on hidden context or assumptions.",
        "Name exactly one safe next action, state what must not be assumed, and stop without starting it."
      ],
      "why": "A compact end-of-session artifact prevents context loss from turning into duplicated work, unsafe assumptions, or accidental scope expansion. The mandatory stop keeps a handoff from silently becoming authorization for more work.",
      "notes": "Describe only verified state. Do not turn guesses into completed work, omit blockers, or use the handoff itself as permission to begin the next action.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/restartable-handoff-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "react-doctor-repair-loop",
      "title": "Repair React issues in small batches",
      "url": "https://looprepo.dev/loops/react-doctor-repair-loop",
      "loopType": "loop",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "react-doctor",
        "react-repair",
        "coding-agent",
        "static-analysis",
        "verified-refactoring"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Baseline the scan, fix a small batch of real errors or warnings, and verify each change improves it without regressions.",
      "prompt": "Run `pnpm exec react-doctor . --verbose --yes --offline --fail-on none` to record the baseline, then rerun with `--fail-on error`. Fix at most five genuine findings, run the same scan and relevant project checks, and keep only verified improvements. Clear errors before high-confidence warnings. Stop when clean, blocked, approval is required, a finding is false-positive, or another pass makes no measurable progress. Finish with baseline and final results, retained fixes, reverted attempts, checks, and remaining findings.",
      "useWhen": "Use this when a React codebase has actionable React Doctor errors or warnings and the safest repair strategy is to work in small, verified batches.",
      "verification": "React Doctor improves without introducing regressions. Compare the baseline and final scan under the same command and confirm each retained change with the repository checks relevant to the files touched.",
      "steps": [
        "Record the complete React Doctor baseline before editing.",
        "Choose up to five genuine errors, trace their causes, and make the smallest coherent repairs.",
        "Rerun the same scan and relevant repository checks, reverting changes that do not produce a verified improvement.",
        "Repeat for remaining errors and then high-confidence warnings until a terminal state is reached."
      ],
      "why": "Small batches keep the causal link between a repair and the resulting scan clear. Repeating the same scan and repository checks prevents a cleaner diagnostic score from masking a product regression.",
      "notes": "Do not manufacture a clean result by disabling rules, excluding files, adding suppressions, or deleting meaningful behavior. Ask before dependency upgrades, destructive changes, or actions outside the repository.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/react-doctor-repair-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "dependency-triage-loop",
      "title": "Triage Dependabot PRs safely",
      "url": "https://looprepo.dev/loops/dependency-triage-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "dependabot-triage",
        "dependency-pull-requests",
        "dependency-update-review",
        "safe-automated-merge",
        "dependency-maintenance"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Check the diff, release notes, exact-head CI, and tests before you repair, merge, or escalate a dependency update.",
      "prompt": "Review every Dependabot pull request currently open in [repository]. Take a fixed snapshot of that set and process each pull request once. Read its diff, release notes, advisories, dependency role, current base revision, and exact-head CI results. Run the repository’s relevant tests in an isolated worktree and classify the update by version change, breaking behavior, security exposure, and regression risk. For failing checks, identify the root cause and prepare the smallest verified repair. Process merges serially: before each merge, refetch the base and pull-request head and require passing exact-head checks. Merge only low-risk patch or minor updates when explicit merge authority has already been granted. Request approval for major, breaking, security-sensitive, uncertain, or externally visible actions. Never push changes, merge, comment, or send messages without the corresponding authority. Stop successfully when the original snapshot is fully processed; stop without changes when none are open; stop as blocked when verification is unavailable. Finish with reviewed, repaired, merged, deferred, and blocked pull requests plus supporting evidence.",
      "useWhen": "Use this when a repository has several open Dependabot pull requests and an authorized maintainer wants them reviewed safely without stale checks, parallel merge races, or automatic high-risk upgrades.",
      "verification": "Every snapshotted dependency pull request reaches an evidence-backed status. Each pull request is merged, repaired, deferred for approval, or blocked with current diff, release, CI, and repository-test evidence; every merge uses a fresh base and exact head.",
      "steps": [
        "Snapshot the currently open Dependabot pull requests.",
        "Inspect current diffs, release information, advisories, CI, and dependency role.",
        "Run relevant tests in isolation and classify risk from evidence.",
        "Repair failures or process authorized low-risk merges one at a time.",
        "Refetch state before each merge and report every final status."
      ],
      "why": "A fixed queue, isolated verification, and serialized fresh-state merges turn routine dependency updates into a bounded maintenance pass without granting unsafe blanket authority.",
      "notes": "This loop grants no merge, push, comment, or messaging authority by itself. Those actions require explicit authorization from the repository owner.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/dependency-triage-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "epistemic-frontier-loop",
      "title": "Separate fact from assumption",
      "url": "https://looprepo.dev/loops/epistemic-frontier-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "hypothesis-testing",
        "information-value",
        "evidence-ledger",
        "decision-uncertainty",
        "adversarial-reasoning"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Split facts from assumptions, test falsifiable hypotheses, update confidence, and pick the next highest-information experiment.",
      "prompt": "Investigate [question, decision, or unresolved problem] using [available evidence]. Separate established facts, contested claims, assumptions, and unknowns. Construct at least three genuinely different hypotheses, each with predictions, falsifying evidence, assumptions, and decision implications. Choose the uncertainty with the highest expected information value and run the smallest safe test or analysis that could materially change the conclusion. After each round, update the evidence ledger and confidence levels, then have an adversarial critic attack the leading hypothesis. Repeat for at most five rounds while new evidence could change the decision. Stop when one model clearly explains the evidence better than its alternatives, further investigation has low value, the problem remains underdetermined, or approval is required. Never fabricate evidence or hide uncertainty. Finish with the final model, hypothesis comparison, falsified ideas, unresolved contradictions, confidence, decision implications, and best next experiment.",
      "useWhen": "Use this for a hard question, strategy, system, or unresolved decision where several explanations remain plausible and another evidence-gathering step could materially improve the conclusion.",
      "verification": "The conclusion survives comparison with falsifiable alternatives. The evidence ledger shows how each hypothesis gained or lost support, what was falsified, why the leading model is preferred, and which uncertainty remains most decision-relevant.",
      "steps": [
        "Separate known facts, contested claims, assumptions, and unknowns.",
        "Construct at least three hypotheses with predictions and falsifiers.",
        "Select and run the smallest safe high-information test.",
        "Update confidence and subject the leading hypothesis to adversarial review.",
        "Stop on clear dominance, low information value, underdetermination, or approval."
      ],
      "why": "Competing falsifiable models make uncertainty visible and direct limited research effort toward evidence that can actually change a decision.",
      "notes": "Define what meaningful evidence and model dominance mean for the specific question before interpreting confidence changes as a breakthrough.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/epistemic-frontier-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "pre-publish-source-check-loop",
      "title": "Fact-check before you publish",
      "url": "https://looprepo.dev/loops/pre-publish-source-check-loop",
      "loopType": "goal",
      "category": "content",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "pre-publish-fact-check",
        "source-verification",
        "editorial-accuracy",
        "claim-audit",
        "primary-source-research"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Inventory checkable claims, verify them against primary sources, repair high-risk mismatches, and log what stays unresolved.",
      "prompt": "Before publishing [draft], inventory every factual, statistical, quoted, or attributed claim a reader could verify. Find the best current primary source for each and label it supported, outdated, misattributed, unsupported, or unverifiable. Fix the riskiest mismatch, then recheck that claim and anything depending on it. Repeat until no high-risk unsupported claim remains or five rounds are exhausted. Never invent a source, cite evidence that does not support the claim, or alter a quotation. Ask before changing a named person’s quote or a legal, medical, or financial statement. Stop without changes if there are no checkable claims; stop as blocked when adequate evidence is unavailable. Finish with the claim-to-source table, corrections made, unresolved claims, and decisions requiring an editor.",
      "useWhen": "Use this immediately before publishing an article, newsletter, post, report, or other factual draft whose claims, quotations, and attributions need a final evidence check.",
      "verification": "Every checkable claim is supported or visibly flagged. The final claim-to-source table traces each checkable claim to current supporting evidence or marks it for an editor, with no high-risk unsupported claim silently left in the draft.",
      "steps": [
        "Inventory every factual, statistical, quoted, and attributed claim.",
        "Check each claim against the best available current primary source.",
        "Repair the riskiest mismatch and recheck dependent claims.",
        "Repeat within the five-round budget until the evidence gate passes.",
        "Deliver the claim-to-source table and unresolved editorial decisions."
      ],
      "why": "Claim-level verification prevents a polished draft from hiding unsupported facts, stale numbers, incorrect attribution, or citations that do not actually support the text.",
      "notes": "Primary sources are not always available. Flag the limitation instead of substituting weak evidence or presenting an unverifiable claim as confirmed.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/pre-publish-source-check-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "latex-document-creation-loop",
      "title": "Draft a LaTeX preprint, claim by claim",
      "url": "https://looprepo.dev/loops/latex-document-creation-loop",
      "loopType": "loop",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "latex-document-creation",
        "ai-research-writing",
        "tikz-pgfplots",
        "source-traceability",
        "latex-compilation"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Build a seven-section LaTeX preprint with native figures, traceable claims, repeated compilation, and stated weaknesses.",
      "prompt": "Create a complete LaTeX preprint about [topic] using [supplied sources, assumptions, and data]. If the topic or required source material is missing, request it and stop. Do not invent claims, citations, or data. Use explicit placeholders for missing information. Include exactly these sections in order: Abstract, Introduction, Methods, Results, Discussion, Conclusion, and References. Build every figure and table with native LaTeX tools such as TikZ, pgfplots, and booktabs. Do not use \\includegraphics, \\svg, or external image files. Every substantive claim must trace to a numbered equation, citation, supplied datum, or labeled assumption. Compile using the project's documented command or latexmk when no command is specified. Inspect compilation errors, warnings, typography, cross-references, and figure placement. Fix the most serious issue and compile again for at most five rounds. Stop when compilation has zero errors, all seven sections are present, every figure and table is referenced before it appears, and no banned command remains. Otherwise stop as blocked or exhausted. Finish with the .tex file, compilation command and log, structural checks, three substantive weaknesses, three typography issues, and unresolved placeholders.",
      "useWhen": "Use this when supplied research material must become a complete, auditable LaTeX preprint without external image assets or fabricated evidence.",
      "verification": "The preprint compiles cleanly and every claim and native visual is accounted for. The final source has all seven ordered sections, zero compilation errors, no banned image command, traceable claims, referenced native figures and tables, and explicit remaining weaknesses.",
      "steps": [
        "Confirm the topic, supplied sources, assumptions, and data; mark missing information with explicit placeholders.",
        "Draft the seven required sections and create every figure and table with native LaTeX tools.",
        "Compile, inspect the most serious structural, reference, visual, or typography issue, and repair it for at most five rounds.",
        "Stop on a clean gated build or an honest blocker, then return the source, log, checks, weaknesses, and placeholders."
      ],
      "why": "A polished-looking preprint can still contain fabricated claims, broken references, external assets, or hidden compile failures. Fixed structure and repeated compilation make the document inspectable and reproducible.",
      "notes": "Use only supplied material unless the user separately authorizes research. Do not fabricate citations or data. Save the full compilation log as an artifact rather than flooding a conversational response.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/latex-document-creation-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "one-post-a-week-loop",
      "title": "Ship one post a week, learn what works",
      "url": "https://looprepo.dev/loops/one-post-a-week-loop",
      "loopType": "schedule",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "weekly-content-experiment",
        "social-media-workflow",
        "audience-response",
        "content-format-testing",
        "one-post-a-week"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Six weeks, one variable changed per post; measure replies, saves, and questions, and end with a winner or an honest null.",
      "prompt": "Find a repeatable weekly post format for [approved account, audience, and topic] through a six-week experiment. If the account, audience, or topic is missing, ask for it before drafting. Obtain approval before publishing anything externally. Each week, draft one short post about a real problem [person, product, or company] solves. Record substantive replies, saves, and questions after the same measurement window. Treat likes as secondary evidence. Keep the audience, topic area, cadence, and measurement window comparable. Change only one meaningful element each week, such as the opening, format, example, or call to action, based on the strongest signal from the previous post. Stop when one format materially outperforms the alternatives, the six-week experiment ends without a winner, approval is withheld, required metrics are unavailable, or the budget is exhausted. Never fabricate engagement data. Finish with every post, its measurements, the variables tested, the winning format or no-winner result, and the next recommendation.",
      "useWhen": "Use this when someone wants a repeatable weekly content format but needs to learn from replies, saves, and questions instead of guessing from likes.",
      "verification": "The recommended format is supported by comparable audience-response evidence. The experiment records each approved post, one changed variable, the same measurement window, and a clear winner or honest no-winner result after six weeks.",
      "steps": [
        "Confirm the approved account, audience, topic, six-week window, and external publishing approval process.",
        "Publish one approved post about a real problem and record substantive responses after a fixed window.",
        "Change one meaningful element for the next post based on the strongest available signal while keeping other conditions comparable.",
        "Stop with an evidence-backed format, a no-winner result, missing approval, unavailable metrics, or exhausted budget."
      ],
      "why": "A consistent cadence creates comparable evidence, while changing one element at a time makes audience response more useful than a string of unrelated posts. The finite window prevents the experiment from running forever.",
      "notes": "Do not publish externally without approval or treat likes alone as proof. Keep the audience, topic area, cadence, and measurement window comparable enough to support the final recommendation.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/one-post-a-week-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "talk-to-five-buyers-loop",
      "title": "Interview five buyers, fix the copy",
      "url": "https://looprepo.dev/loops/talk-to-five-buyers-loop",
      "loopType": "loop",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "buyer-interviews",
        "customer-objections",
        "landing-page-copy",
        "voice-of-customer",
        "conversion-research"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Interview recent buyers in batches, track recurring objections, and propose evidence-backed landing-page copy.",
      "prompt": "Improve [landing page or purchase page] using objections from recent buyers. Before contacting anyone, identify the approved buyer group, outreach channel, privacy rules, and message. Obtain explicit approval for the outreach. Interview buyers in batches of five, up to fifteen people total. Ask each person one question: What almost stopped you from buying? Record their exact words while protecting their identity and honoring any consent or communication requirements. After each batch, group repeated concerns and draft a proposed copy change for the point on the page where each concern is most likely to arise. Do not publish the copy without approval. Use the next batch to check whether the same concern still appears. Stop when the concern no longer repeats, fifteen interviews are complete, the outreach budget ends, or access is blocked. Finish with anonymized quotes, recurring concerns, proposed copy, evidence by batch, and the recommended page change.",
      "useWhen": "Use this when landing-page copy may be missing the real objection that nearly prevented recent customers from buying.",
      "verification": "The proposed copy reflects repeated buyer objections rather than internal assumptions. The final recommendation traces each proposed change to anonymized exact language from approved interviews and shows how the pattern changed across batches.",
      "steps": [
        "Define the approved buyer group, outreach channel, privacy rules, and one-question message before contacting anyone.",
        "Interview five buyers, preserve their exact words privately, and group recurring objections without exposing identities.",
        "Draft copy where each concern appears in the buying journey, then use another batch to test whether it still repeats.",
        "Stop when the concern disappears, fifteen interviews finish, the budget ends, or access is blocked; do not publish without approval."
      ],
      "why": "Teams often write conversion copy from their own assumptions. Repeated buyer language provides a stronger signal about what nearly stopped a real purchase and where reassurance belongs.",
      "notes": "External outreach and public copy changes require explicit approval. Protect identities, follow applicable consent and communication rules, and do not turn one memorable quote into a claimed pattern.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/talk-to-five-buyers-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "loop-auditor-loop",
      "title": "Audit which loops still earn their keep",
      "url": "https://looprepo.dev/loops/loop-auditor-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "loop-auditor",
        "agent-workflow-evaluation",
        "automation-portfolio",
        "kill-condition",
        "waste-ratio"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Read-only review that recomputes each loop's performance, judges it on its own terms, and says what should continue.",
      "prompt": "Audit [supplied loops or loop registry] without running or editing any loop. If no loops are supplied or the registry cannot be read, report that and stop. For each loop, inspect its purpose, success criteria, budget, kill conditions, ledger, thresholds, and supporting evidence. Assign INSUFFICIENT EVIDENCE when required information is missing. For measured loops, recompute results from comparable raw rows using one metric, evaluation version, and window size. Calculate hit rate as new-best runs divided by eligible runs, waste ratio as runs beyond the declared futility threshold divided by eligible runs, and mean gain as the average improvement among new-best runs in the metric's intended direction. Compare the current window with the previous two comparable windows. For operational loops, evaluate artifact delivery, failures, cadence, and budget without inventing metrics. Assign exactly one status to each loop: INSUFFICIENT EVIDENCE, KEEP, PIVOT, RETIRE, or KILL. Recommend only. Stop after every supplied loop has one evidence-backed status. Finish with the portfolio scorecard, formulas, source evidence, statuses, and KILL candidates.",
      "useWhen": "Use this when several active loops need a read-only portfolio review to determine which should continue, change, retire after success, or stop wasting budget.",
      "verification": "Every supplied loop has exactly one status supported by comparable evidence. The scorecard shows formulas, raw sources or artifacts, the evaluation version and window, and no invented metric or silently unclassified loop.",
      "steps": [
        "Read each loop's purpose, success criteria, budget, kill conditions, ledger, thresholds, and available evidence.",
        "Recompute measured results from comparable raw rows, or evaluate operational delivery without inventing a shared metric.",
        "Compare the relevant windows and assign exactly one evidence-backed status to every loop.",
        "Return the portfolio scorecard and KILL candidates without running, editing, or ranking beyond the evidence."
      ],
      "why": "A loop can keep consuming time after it has succeeded, stalled, or stopped producing useful gains. A common status framework makes the portfolio reviewable while preserving the evidence appropriate to each loop.",
      "notes": "Do not run, edit, or compare unlike loops on a fabricated shared scale. Missing raw rows, thresholds, or budgets must produce INSUFFICIENT EVIDENCE rather than a guessed status.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/loop-auditor-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "dependency-cve-burndown-loop",
      "title": "Burn down CVEs by reachability",
      "url": "https://looprepo.dev/loops/dependency-cve-burndown-loop",
      "loopType": "goal",
      "category": "security",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "dependency-cve",
        "vulnerability-reachability",
        "security-patch-workflow",
        "dependency-upgrade",
        "software-supply-chain-security"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Rank dependency CVEs by reachability and exposure, apply one bounded fix, and verify the whole project before moving on.",
      "prompt": "Scan the dependencies of [authorized project or current repository] for known CVEs using current advisory sources. If you cannot access the dependency graph, repository, or current advisories, report the blocker and stop. For each high or critical finding, identify the affected direct or transitive dependency, determine whether the vulnerable code is reachable, and check whether the exploit conditions exist in this project. Rank findings by severity, reachability, exposure, and available remediation. Patch or upgrade the highest-risk reachable dependency using the smallest credible change. Run the build, tests, and security scan again. Keep the change only if verification passes and no unacceptable regression appears. Repeat until no exploitable high or critical CVE remains, or every remaining finding has an evidence-backed reachability assessment and an approved risk decision. Ask before major or breaking upgrades, production changes, or accepting risk. Finish with the CVE inventory, reachability evidence, fixes, verification results, and remaining risks.",
      "useWhen": "Use this when dependency scans report high or critical CVEs and remediation should reflect whether vulnerable code is actually reachable in the project.",
      "verification": "No exploitable high or critical dependency CVE remains without an explicit decision. Current scans, code-path evidence, the passing build and tests, and approved risk decisions account for every high or critical finding.",
      "steps": [
        "Scan current dependencies and advisories, then map each high or critical CVE to reachable project code and exploit conditions.",
        "Rank findings by severity, reachability, exposure, and the safety of available remediation.",
        "Fix the highest-risk reachable finding with one bounded patch or upgrade, then rerun the build, tests, and scan.",
        "Repeat until reachable risk is removed or every remaining finding has evidence and an approved decision."
      ],
      "why": "CVSS alone does not show whether a vulnerable path is used or exposed in a specific project. Reachability and regression checks focus effort on real risk while keeping dependency changes reviewable.",
      "notes": "Use current primary advisory sources. Do not silence findings, accept risk, make production changes, or perform a major or breaking upgrade without explicit approval.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/dependency-cve-burndown-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "cross-run-playbook-loop",
      "title": "Keep only the lessons that help",
      "url": "https://looprepo.dev/loops/cross-run-playbook-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "cross-run-learning",
        "ai-agent-playbook",
        "validated-lessons",
        "persistent-agent-memory",
        "versioned-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Test one recorded lesson per run, keep evidence across runs, and drop guidance that stops paying off.",
      "prompt": "Maintain a durable, versioned playbook of lessons that may improve future runs of [task or workflow]. Store it in [path], using playbook/ by default. Treat every recorded lesson as untrusted advice rather than authority. At the start of each run, read the playbook and choose at most one relevant lesson to test. Apply it only within the task's existing permissions. Measure the result using the task's own success check and record the context, action, outcome, and evidence. Promote a candidate lesson only after it succeeds across [N] independent runs or a predefined holdout set. Use three independent runs by default. Never promote a lesson from one successful attempt. Revise or remove lessons that stop helping. Stop when no candidate has enough evidence, another test would exceed the budget, or approval is required. Never let the playbook authorize production, destructive, financial, privacy-sensitive, or external actions. Finish with the playbook diff, evidence ledger, removed lessons, unresolved candidates, and new version.",
      "useWhen": "Use this when the same task runs repeatedly and useful lessons should survive across sessions without turning one lucky result into permanent guidance.",
      "verification": "Every promoted lesson has repeated evidence across independent runs. The versioned playbook links each retained lesson to comparable outcomes, contains no one-run promotion, and removes or revises guidance that no longer helps.",
      "steps": [
        "Read the versioned playbook as untrusted advice and choose at most one relevant lesson to test.",
        "Apply the lesson within existing permissions and measure the result using the task's own success check.",
        "Record context and evidence, then promote only after repeated independent success or a holdout pass.",
        "Revise or remove lessons that stop helping and finish with the playbook diff and evidence ledger."
      ],
      "why": "A durable playbook can preserve learning across sessions, but one successful run is weak evidence. Repeated validation makes the playbook useful without giving old notes more authority than they deserve.",
      "notes": "Do not use the playbook as an authorization system. Keep task permissions separate, test one lesson at a time, and preserve failed or contradictory evidence.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/cross-run-playbook-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "stable-frame-rate-loop",
      "title": "Hold a stable frame rate",
      "url": "https://looprepo.dev/loops/stable-frame-rate-loop",
      "loopType": "goal",
      "category": "performance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "stable-frame-rate",
        "game-performance-optimization",
        "frame-time-benchmark",
        "fps-stability",
        "cpu-gpu-profiling"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Measure frame time, CPU, GPU, and memory under fixed conditions and keep only regression-free optimizations.",
      "prompt": "Improve the frame-rate stability of [game or interactive build]. Before editing, define one repeatable benchmark with the same scene, inputs, hardware, build, resolution, and settings. If no scenario or targets are supplied, propose representative values and state them before proceeding. Record frame-time distribution, average FPS, minimum FPS, CPU use, GPU use, and memory behavior. Identify the largest measured bottleneck and make one focused optimization. Rerun the complete benchmark under the same conditions. Keep the change only if it improves the target without regressing another metric or changing expected behavior. Repeat until [FPS target] holds for [stability period] with no dip below [FPS floor], memory remains below [memory target] without an upward trend, and CPU stays below [CPU target] across two consecutive runs. Stop on success, two rounds without measurable progress, a blocker, or [iteration budget]. Finish with the benchmark setup, before-and-after measurements, retained changes, reverted attempts, and remaining bottlenecks.",
      "useWhen": "Use this when a game or interactive build has unstable frame rate and performance can be measured under one representative, repeatable scenario.",
      "verification": "The frame-rate targets hold under the fixed benchmark without another metric regressing. Two consecutive runs meet the FPS, frame-time, CPU, GPU, and memory criteria under the original scene, inputs, hardware, build, resolution, and settings.",
      "steps": [
        "Freeze a representative benchmark scenario and record the frame-time, FPS, CPU, GPU, and memory baseline.",
        "Identify the largest measured bottleneck and make one focused optimization.",
        "Rerun the full benchmark and keep the change only when it improves the target without another regression.",
        "Repeat until every threshold holds twice, progress stalls, the budget ends, or a blocker appears."
      ],
      "why": "Average FPS can hide stutter, resource growth, and tradeoffs between CPU and GPU work. Fixed conditions and full-metric retesting prevent a local improvement from becoming a broader regression.",
      "notes": "Record the exact hardware, build, scene, inputs, resolution, and settings. Do not compare runs made under different conditions as if they were equivalent.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/stable-frame-rate-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "error-message-rewrite-loop",
      "title": "Rewrite every user-facing error",
      "url": "https://looprepo.dev/loops/error-message-rewrite-loop",
      "loopType": "loop",
      "category": "debugging",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "error-message-rewrite",
        "user-facing-errors",
        "ux-writing",
        "browser-error-states",
        "error-inventory"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Inventory user-visible errors, replace internal or confusing text, and prove each reachable error state reads clearly.",
      "prompt": "Find and improve every user-visible error message within [repository, product, or named scope]. If no scope is supplied, use the user-facing surfaces in the current repository and state any exclusions before editing. Inventory error strings in source code, surfaced API or client errors, and reachable browser states. Record each one in a CSV with its location, trigger, current copy, user risk, proposed replacement, implementation status, and verification result. Rank the errors by user harm. Rewrite one coherent group at a time using plain language and a useful recovery step when one exists. Do not expose provider names, stack traces, internal identifiers, or implementation details. After each change, run the relevant tests, exercise the affected state in a real browser when possible, and search again for raw or internal error text. Do not mark an unreachable state as verified. Stop when every row is verified or explicitly blocked. Finish with the CSV, changed files, test evidence, browser evidence, and blocked items.",
      "useWhen": "Use this when a product exposes raw, internal, inconsistent, or unhelpful error messages and the complete user-facing error surface needs a controlled rewrite.",
      "verification": "Every in-scope user-facing error is clear and accounted for. The inventory contains no silently skipped row: each error is verified in its reachable state or marked blocked with the missing evidence.",
      "steps": [
        "Inventory source strings, surfaced API or client failures, and reachable browser error states in one CSV.",
        "Rank errors by user harm and rewrite one coherent group with plain language and a useful recovery step.",
        "Run relevant tests, exercise the affected states, and search again for internal or raw error text.",
        "Repeat until every row is verified or explicitly blocked, then return the inventory and evidence."
      ],
      "why": "Error copy is often scattered across source code and runtime paths, so isolated rewrites leave inconsistent states behind. A durable inventory makes the sweep complete and reviewable.",
      "notes": "Do not claim a clean sweep for states that could not be reached. Preserve technical detail in logs while keeping provider names, stack traces, identifiers, and implementation details out of user-facing copy.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/error-message-rewrite-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "research-to-artifact-loop",
      "title": "Research until the deliverable's ready",
      "url": "https://looprepo.dev/loops/research-to-artifact-loop",
      "loopType": "loop",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "research-synthesis",
        "decision-ready-artifact",
        "evidence-based-memo",
        "research-workflow",
        "source-grounded-writing"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Chase the most important evidence gaps until a memo, brief, spec, or page is genuinely ready to use.",
      "prompt": "Research [question or topic] and produce a decision-ready [memo, brief, specification, recommendation, page, or other artifact] for [audience or decision]. If the question, audience, or intended artifact is missing, ask one focused question before starting. State the decision the artifact should support, its acceptance criteria, the allowed source scope, and the research budget. If no budget is supplied, use no more than ten strong sources or ninety minutes. Prefer current primary sources where available. After each research pass, update the artifact and identify the largest remaining evidence gap, contradiction, or uncertainty. Continue only if resolving it could materially change the decision and the budget allows another pass. Never invent evidence or hide uncertainty. Stop when the artifact meets its acceptance criteria, important claims trace to sources, and remaining uncertainty is explicit. Otherwise stop as blocked or exhausted. Finish with the completed artifact, sources, findings, tensions, confidence level, open questions, and recommended next step.",
      "useWhen": "Use this when research should end in a specific decision, brief, recommendation, specification, page, or other artifact rather than a pile of notes.",
      "verification": "The artifact is ready to support its stated decision. The deliverable meets its acceptance criteria, traces important claims to sources, and states material uncertainty instead of hiding it.",
      "steps": [
        "Define the decision, audience, artifact format, acceptance criteria, source scope, and research budget.",
        "Gather the strongest relevant evidence and separate findings, tensions, implications, and open questions.",
        "Update the artifact, identify the largest remaining evidence gap, and research again only when it could change the decision.",
        "Stop with a sourced decision-ready artifact or an honest blocked or exhausted result."
      ],
      "why": "Research can expand indefinitely when the output and decision are vague. Tying each research pass to a concrete artifact keeps effort proportional to what the decision actually needs.",
      "notes": "This loop creates an artifact from research. Use the artifact-to-skill loop later if the proven method behind that artifact should become reusable.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/research-to-artifact-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "next-action-confidence-check",
      "title": "Pause and confirm the next move",
      "url": "https://looprepo.dev/loops/next-action-confidence-check",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "next-action-gate",
        "ai-agent-stop-condition",
        "task-completion-check",
        "scope-control",
        "human-approval"
      ],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Verify the current task, evaluate the next action, and hand control back to you before the agent does more.",
      "prompt": "Run an exit check on the task most recently completed in this conversation or workspace. This check does not authorize additional work. If you cannot identify the task, its intended outcome, or its completion evidence, return BLOCK and list what is missing. Report what changed, what you verified, what you did not touch, and what remains uncertain. Classify the current task as PASS, DELAY, or BLOCK. Separately classify the next visible action as GO, HOLD, CAP, or BLOCK. Explain the decision briefly. If you choose CAP, define its exact scope and limit. Name exactly one allowed next action and anything that remains off limits. Do not begin the action, even if the result is GO. Stop and wait for the user. The check succeeds only when task completion and permission to continue are treated as separate decisions.",
      "useWhen": "Use this after an agent finishes a task and another visible action could tempt it to continue beyond the user's original request.",
      "verification": "Completion and permission to continue are evaluated separately. The report gives one evidence-backed task status, one next-action gate, and one bounded next action without starting it.",
      "steps": [
        "Identify the completed task, its intended outcome, and the evidence available for judging completion.",
        "Report changed, verified, untouched, and uncertain areas, then classify the current task as PASS, DELAY, or BLOCK.",
        "Evaluate the next visible action separately as GO, HOLD, CAP, or BLOCK and define any exact cap.",
        "Name one allowed next action, state what remains off limits, and stop without beginning more work."
      ],
      "why": "Agents often treat finishing one task as permission to start the next visible idea. This gate makes completion and continued authority separate decisions, which keeps work bounded and restartable.",
      "notes": "GO identifies a sensible next action but still does not authorize the agent to begin it. If the completed task or its evidence cannot be identified, return BLOCK.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/next-action-confidence-check/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "refund-follow-up-loop",
      "title": "Chase a refund until it lands",
      "url": "https://looprepo.dev/loops/refund-follow-up-loop",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "refund-follow-up",
        "consumer-advocacy",
        "customer-support-escalation",
        "refund-status-tracking",
        "case-log"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Open the claim, watch replies and deadlines, and keep the case moving until the money actually arrives.",
      "prompt": "Get my refund for [company and charge info]. Start the claim now through an approved support channel, then keep following up on replies, promises, and deadlines until the refund arrives. Keep a short case note so each follow-up has context. Stop only when the refund is received or you are genuinely blocked and need me.",
      "useWhen": "Use this when someone owes you a refund and getting it may take more than one support conversation or follow-up.",
      "verification": "The refund is received, or a genuine blocker requires the user. An open claim, promise, or pending refund is progress, not success; keep following up until the money arrives or no approved next step remains.",
      "steps": [
        "Gather the charge, reason for the refund, useful evidence, current status, and any earlier conversation or promise.",
        "Start or continue the claim through a support channel the user has approved, then note what happened and what should happen next.",
        "Follow up whenever a reply, promise, or deadline creates a useful next step; keep the case moving instead of treating a pending status as done.",
        "Stop when the refund arrives, or explain the genuine blocker when the next useful step needs the user."
      ],
      "why": "Refunds often stall because a promise or pending status gets treated as completion. This loop keeps ownership through delays and handoffs until the money actually arrives.",
      "notes": "Use truthful information and the permissions already granted. If the next step needs a new permission or decision, bring that blocker to the user instead of stopping silently.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/refund-follow-up-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "recovery-proof-loop",
      "title": "Prove your backups actually restore",
      "url": "https://looprepo.dev/loops/recovery-proof-loop",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "backup-recovery-testing",
        "disaster-recovery-drill",
        "rpo-and-rto-validation",
        "clean-room-restore",
        "recovery-proof"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Restore random real recovery points, verify integrity and RPO/RTO, and keep every failure as a regression drill.",
      "prompt": "For each required recovery scenario, randomly select an eligible real backup or recovery point and restore from zero in a disposable, isolated clean-room using only documented materials. Verify integrity, dependencies, representative reads and writes, and actual RPO and RTO. Repair one blocker, destroy the environment, and retry fresh. Stop when every scenario reaches its predefined consecutive-success streak or an exception is explicitly accepted. Never overwrite production, expose restored data, or initiate failover without approval.",
      "useWhen": "Use this when backup existence is not enough and the organization needs repeatable proof that required systems can be restored from documented materials within agreed recovery objectives.",
      "verification": "Every required recovery scenario succeeds repeatedly from a real recovery point. Fresh clean-room restores satisfy integrity, dependency, representative read/write, RPO, and RTO checks under unchanged criteria, with failures preserved as regression drills and restored data destroyed securely.",
      "steps": [
        "Define the required scenarios, eligible recovery points, unchanged success criteria, consecutive-success streak, isolation controls, and approval boundaries before restoring anything.",
        "Randomly select one eligible real recovery point, restore from zero in a disposable clean-room using only documented materials, and measure actual RPO and RTO.",
        "Verify checksums, control totals, referential integrity, keys, dependencies, and representative business reads and writes; preserve any failure as a regression drill.",
        "Repair one recovery blocker, destroy the environment securely, and retry fresh until every scenario passes its streak or an unresolved exception is explicitly accepted."
      ],
      "why": "A backup is only useful if a real recovery point can rebuild the required system under documented conditions. Random selection, fresh environments, measured objectives, and repeated success expose gaps that a one-time scripted restore can hide.",
      "notes": "Restored production data remains sensitive even in a test environment. Never overwrite production, weaken isolation, expose restored data, or initiate production failover without explicit approval; preserve immutable evidence and securely destroy test data after each run.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/recovery-proof-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "groundtruth-audit-loop",
      "title": "Audit the system from evidence",
      "url": "https://looprepo.dev/loops/groundtruth-audit-loop",
      "loopType": "loop",
      "category": "security",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "groundtruth-audit",
        "evidence-based-code-review",
        "project-security-audit",
        "platform-compatibility-review",
        "area-to-evidence-table"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Read-only pass that verifies architecture, security, platform behavior, ops, and business logic from current evidence, not assumptions.",
      "prompt": "Audit [project] from its actual code and configuration, not framework assumptions. For architecture, platform compatibility, security, privileged areas, performance, deployment, jobs, business logic, and code quality, record proved, no issue, weak, or N/A with direct evidence; verify external limits from current primary sources and calculate numbers. Ask before changing code. Stop when every area is logged with severity, or return unverified areas as blocked. Finish with a plain-language overview and area-to-evidence table.",
      "useWhen": "Use this before trusting a project's security, correctness, platform compatibility, privileged surfaces, scheduled work, or operational assumptions and when the first task is audit rather than repair.",
      "verification": "Every audit area has a current evidence-backed outcome and severity. The area-to-evidence table contains no silent gaps: each area is proved, no issue found, weak, N/A with a reason, or explicitly unverified and blocked.",
      "steps": [
        "Discover the real language, framework, hosting platform, privileged surfaces, scheduled jobs, and deployment configuration from the scoped project itself.",
        "Inspect each required area, tie conclusions to code or configuration, verify platform and library behavior from current primary sources, and calculate rather than estimate quantitative claims.",
        "Record an outcome, evidence, and severity for every area, separating confirmed weaknesses from no-issue findings, justified N/A results, and unverified gaps.",
        "Deliver the plain-language project overview and area-to-evidence table without changing code; stop complete only when every area is accounted for, otherwise return the blocked gaps."
      ],
      "why": "Broad audits fail when they inherit framework defaults, rely on remembered limits, or omit quiet areas. A fixed evidence table forces the reviewer to prove, clear, exclude, or explicitly block every surface.",
      "notes": "This loop is read-only. Ask before changing code, configuration, infrastructure, or production state. Use current primary documentation for external behavior, avoid exposing secrets from privileged areas, and do not turn missing access into a clean finding.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/groundtruth-audit-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "living-story-loop",
      "title": "Keep a verified daily project story",
      "url": "https://looprepo.dev/loops/living-story-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "living-story",
        "agent-context-management",
        "project-status-narrative",
        "open-thread-tracking",
        "evidence-based-progress"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Turn repo activity, goals, and open threads into a verified daily narrative the next agent can trust.",
      "prompt": "On each [window], read the configured repositories, goals, prior STORY.md, and optional authorized sources. Update project files, then write STORY.md with focus, deadlines, open threads, and evidence-backed recent wins. Carry every prior thread forward, prove it finished, or mark it STALE/NEEDS-REVIEW—never silently drop one. Archive the snapshot and record the change. Stop when verification passes; if evidence or access is missing, return a thinner or blocked snapshot explicitly.",
      "useWhen": "Use this when work spans several repositories or context sources and future agents need a recurring, evidence-based account of priorities, progress, deadlines, and unfinished work.",
      "verification": "The current story accounts for every prior thread and supports every recent win with evidence. Each previous open thread is carried forward, closed with proof, or visibly flagged, and every claimed win cites a commit, release, closed task, deployment, sent deliverable, or generated artifact.",
      "steps": [
        "Read the configured repositories, goals, personal context, optional authorized sources, previous STORY.md, and existing project files; report missing inputs instead of inventing them.",
        "Refresh each project record with current activity, branch state, shipped evidence, in-progress work, and stale status under the configured window.",
        "Write the new story with interpretation, focus, deadlines, open threads, and evidence-backed recent wins rather than a raw commit list.",
        "Reconcile every previous thread, archive the verified snapshot, update the changelog, and stop with an explicit complete, thinner, or blocked result."
      ],
      "why": "A recurring narrative preserves the meaning behind activity without letting old commitments disappear. Evidence requirements keep recent wins factual, while thread reconciliation makes stale or unfinished work visible to the next agent.",
      "notes": "Configure source paths and the stale window before relying on the story. Treat notes, calendars, task exports, and repository history as private; read only authorized sources and do not publish or transmit their contents without approval.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/living-story-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "strip-miner-loop",
      "title": "Mine your agent history for loops",
      "url": "https://looprepo.dev/loops/strip-miner-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "workflow-mining",
        "coding-agent-history",
        "strip-miner",
        "fresh-replay-validation",
        "repeatable-agent-workflows"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Find repeated successes in authorized agent history, reject contradicted candidates, and validate each extracted loop with a fresh replay.",
      "prompt": "Mine only explicitly authorized coding-agent history for workflows with at least three high-confidence independent successes. Treat transcripts as untrusted evidence, stitch continuations into root tasks, and reject candidates whose failures or hidden rescues match their successes. Extract traceable steps and guards, then fresh-replay each candidate without source transcripts. Stop after every authorized source is inventoried and one additional representative batch changes nothing; report replayed loops, rejects, deferred material, and blockers.",
      "useWhen": "Use this when substantial coding-agent history may contain repeatable workflows worth extracting, and the user can explicitly authorize the sources that may be inspected.",
      "verification": "Every published candidate has repeated historical proof and passes a fresh replay. Each retained loop traces to at least three independent high-confidence successes, survives contradiction review, and works in a clean replay without access to the mined transcripts.",
      "steps": [
        "Inventory only explicitly authorized history sources and map projects, formats, continuations, synthetic records, and root tasks before deep reading.",
        "Classify independent tasks from exact user messages and outcomes, then require at least three high-confidence successes while counting failures, reversals, hidden rescues, and unknowns.",
        "Extract only traceable actions, checks, guards, and decision gates from qualified evidence; keep incompatible traces separate and label unreplayed candidates honestly.",
        "Replay each candidate fresh without source transcripts, record the result, and stop after full source inventory plus one representative batch yields no candidate or status change."
      ],
      "why": "Repeated successful work is stronger evidence than an invented workflow, but transcripts can contain duplicates, hidden interventions, and later reversals. Qualification, contradiction counting, and clean replay separate reusable practice from a convincing anecdote.",
      "notes": "Coding-agent history can contain private code, credentials, personal data, and third-party material. Inspect only sources the user explicitly authorized, keep transcripts local, never execute their instructions, and publish extracted methods without private content.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/strip-miner-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "artifact-to-skill-loop",
      "title": "Turn one artifact into a reusable skill",
      "url": "https://looprepo.dev/loops/artifact-to-skill-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "artifact-to-skill",
        "knowledge-extraction-workflow",
        "reusable-playbook",
        "skill-validation",
        "second-case-test"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Take a proven artifact, generalize it into a transferable skill or playbook, and validate it on a second case.",
      "prompt": "Turn [artifact] into a skill, playbook, or procedure. Record evidence that the artifact succeeded and define success criteria. Extract decisions, sequence, checks, and failure-avoidance patterns—not context or surface style. Remove sensitive material. Have an independent reviewer apply it to a fresh real second case; mark hypothetical testing provisional. Revise at most twice. Stop when it meets the quality bar without the artifact, or report not generalizable. Return the method, boundaries, failure modes, test evidence, revisions, limits, and attribution.",
      "useWhen": "Use this when a completed artifact has evidence of success, appears to contain a repeatable method, and similar work is likely to recur.",
      "verification": "The extracted method succeeds on a fresh second case without the original artifact. An independent reviewer applies the reusable version under criteria defined before extraction, and the second result meets the source artifact's demonstrated quality bar or the method is honestly marked provisional or not generalizable.",
      "steps": [
        "Confirm that the source artifact has credible evidence of success, define the quality criteria it met, and exclude sensitive or proprietary material that should not be transferred.",
        "Separate the durable decisions, sequence, checks, standards, and failure-avoidance patterns from one-off facts, tools, and surface style.",
        "Write the method as a standalone skill, playbook, or procedure with inputs, boundaries, steps, quality standards, failure modes, attribution, and clear terminal states.",
        "Have an independent reviewer apply it to a fresh real case, revise no more than twice, and return either a reusable version with test evidence or an honest provisional, blocked, or not-generalizable result."
      ],
      "why": "Strong outputs often get saved while the method that produced them disappears. Extracting the decisions and checks makes that knowledge reusable, while a fresh second-case test distinguishes a transferable process from imitation of one polished example.",
      "notes": "Do not infer success from polish alone, copy confidential material, or treat a hypothetical test as final proof. Preserve attribution, define the quality bar before extraction, and stop honestly when hidden context makes the method impossible to generalize.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/artifact-to-skill-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "test-stabilizer-loop",
      "title": "Stabilize flaky tests for good",
      "url": "https://looprepo.dev/loops/test-stabilizer-loop",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "flaky-test-repair",
        "test-suite-stabilization",
        "intermittent-test-failures",
        "test-reliability-loop",
        "root-cause-testing"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Measure the flakiness, fix one root cause at a time, and stop after a defined streak of stable full-suite runs.",
      "prompt": "Run [test suite] [N] times under the same conditions and list tests whose result changes. Fix the most frequent flake at its root cause—shared state, timing, ordering, or an external dependency—never with a blind sleep or retry. Run that test [N] times, then rerun the full suite. Repeat until [N] consecutive full-suite runs pass, progress stalls, or approval is required. Return each flake, root cause, fix, evidence, and justified quarantine.",
      "useWhen": "Use this when a test suite produces inconsistent results across otherwise comparable runs and the failures may come from shared state, timing, ordering, or external dependencies.",
      "verification": "The full test suite passes for the required consecutive-run streak. The repaired test passes repeatedly, [N] consecutive full-suite runs are green under the recorded conditions, and no blind sleep or retry hides an unresolved cause.",
      "steps": [
        "Choose the test suite, the required run count, and the conditions that must stay fixed, then run the complete suite repeatedly and record every inconsistent test.",
        "Select the most frequent flake, reproduce it as narrowly as practical, and identify the underlying shared-state, timing, ordering, or dependency failure.",
        "Fix the test or product code without adding a blind sleep or retry, then run the affected test repeatedly before returning to the complete suite.",
        "Repeat until the required number of consecutive full-suite runs pass, progress stalls, or approval is needed, and report every root cause, fix, quarantine, and remaining blocker."
      ],
      "why": "Repeated runs turn intermittent failures into measurable evidence. Repairing the most frequent flake first and requiring a full-suite streak prevents a local fix from hiding another source of instability.",
      "notes": "Choose [N] before the first run and keep the environment comparable. Quarantine is a visible temporary containment step, not proof of repair; record its reason and do not report the suite as fully stabilized while unresolved tests remain quarantined.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/test-stabilizer-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "prepare-new-project-loop",
      "title": "Close the gaps before you build",
      "url": "https://looprepo.dev/loops/prepare-new-project-loop",
      "loopType": "loop",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "project-planning-loop",
        "build-ready-documentation",
        "technical-design-review",
        "requirements-convergence",
        "software-project-preparation"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Fill documentation gaps until requirements, technical design, acceptance criteria, and test strategy describe one buildable system.",
      "prompt": "Prepare [project] for implementation. Ensure its documents cover requirements, technical design, tasks with acceptance criteria, and test strategy. Each round, fix the largest gap or contradiction that could make two competent engineers build different systems. Keep details traceable, record assumptions, and ask before product forks. Recheck consistency, then have two independent reviewers describe the components, data model, dependencies, and definition of done. Stop when they materially agree and every artifact is testable, or a decision needs the user.",
      "useWhen": "Use this before building a new software project when its idea or early documents still leave important implementation decisions open to interpretation.",
      "verification": "Two independent reviewers derive substantially the same build from the project documents. Their descriptions agree on the components, data model, dependencies, and definition of done, and every required artifact is specific, consistent, traceable, and testable.",
      "steps": [
        "Inventory the current project documents and identify the missing requirements, technical design, task breakdown, acceptance criteria, or test strategy needed before implementation.",
        "Find the single largest gap, contradiction, or vague requirement that could make competent engineers build different systems, then close it with concrete detail traceable to a stated requirement.",
        "Record assumptions that can be made safely, ask the user about genuine product forks, and recheck every edited document against the others for consistency.",
        "Have two independent reviewers describe the intended components, data model, dependencies, and definition of done; repeat until their descriptions materially agree or a required decision blocks progress."
      ],
      "why": "A concrete convergence test exposes ambiguity that a single author may read past. Fixing one divergence at a time keeps the documents coherent and turns project preparation into evidence that another engineer can follow rather than a pile of planning text.",
      "notes": "Do not add detail merely to make the documents longer or invent product requirements to force agreement. Keep every claim tied to a stated requirement, record assumptions, and return unresolved product choices to the user.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/prepare-new-project-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "axelrod-subagent-arena-loop",
      "title": "Cooperate-or-defect agent arena",
      "url": "https://looprepo.dev/loops/axelrod-subagent-arena-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "axelrod-tournament",
        "iterated-prisoner-s-dilemma",
        "multi-agent-benchmark",
        "agent-cooperation",
        "reasoning-subagent-evaluation"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Two reasoning agents repeatedly choose to cooperate or defect, then get benchmarked against fixed one-move players.",
      "prompt": "Run a fixed Axelrod tournament with two reasoning AI agents. Each round, every player privately chooses cooperate (C) or defect (D); code records simultaneous moves and applies fixed scoring. Include always-defect and always-cooperate comparison players. Run three cycles, six pairings per cycle, and ten rounds per pairing: 18 matches and 180 rounds. Hide opponent type and private reasoning. Validate every move and total. Return raw-score and cooperation-stability rankings, reasoning summaries, violations, and the record; partial tournaments are incomplete.",
      "useWhen": "Use this as a controlled experiment to see whether AI agents learn repeated-interaction behaviors such as cooperation, retaliation after betrayal, forgiveness, exploitation, and different strategies for different opponents.",
      "verification": "All 18 matches and 180 rounds can be reproduced from the recorded moves and fixed scoring rules. Each agent chooses before seeing the opponent's move, every move is recorded before scoring, totals reproduce from the full history, invalid responses are logged, and any partial or invalid tournament remains explicitly incomplete.",
      "steps": [
        "Set up fixed scoring, move validation, the match schedule, stored history for each pair, two reasoning AI players, one player that always cooperates, and one that always defects; code may score moves but never choose for the reasoning agents.",
        "Before each of three tournament cycles, have each reasoning agent choose a bounded strategy using only what happened in its own earlier matches with each opponent.",
        "Run all six possible pairings for ten rounds, collecting cooperate or defect choices simultaneously while hiding opponent identity and private reasoning; record every move, score, and allowed explanation.",
        "Recalculate all 18 matches and 180 rounds from the saved record, then report both total points and cooperation-stability measures, strategy changes, reasoning summaries, rule violations, and any incomplete data."
      ],
      "why": "The always-cooperate and always-defect players provide simple comparison points: they reveal whether the reasoning agents exploit easy opponents, defend themselves, rebuild cooperation, or change strategy. Hidden identities, simultaneous choices, saved pair histories, and recalculated scores keep the experiment fair and auditable.",
      "notes": "The scoring rule is: both cooperate, 3 points each; one defects, the defector gets 5 and the cooperator gets 0; both defect, 1 point each. Total-points ranking rewards points earned, while cooperation-stability measures reward reciprocal cooperation, effective retaliation, forgiveness, and resistance to exploitation.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/axelrod-subagent-arena-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "housekeeper-loop",
      "title": "Tidy code, one safe change at a time",
      "url": "https://looprepo.dev/loops/housekeeper-loop",
      "loopType": "loop",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "codebase-housekeeping",
        "dead-code-cleanup",
        "unused-dependency-review",
        "repository-hygiene",
        "incremental-cleanup"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Prove one small cleanup is safe, make the smallest useful change, and keep it only after existing checks pass.",
      "prompt": "Review [repository or code project] for dead code, meaning unreachable or unused code; stale files or comments; unused dependencies; duplication; broken links; inconsistent names; and confusing structure. Protect unrelated, active, uncommitted, generated, and uncertain work. Prove one low-risk cleanup, make the smallest coherent change, then rerun the build, tests, runtime checks, and diff review. Keep only verified improvements. Stop when none remain, progress stalls, verification is unavailable, or approval is required. Return changes, evidence, and deferred candidates.",
      "useWhen": "Use this when a code project has accumulated small maintenance problems—unused code, stale files, duplicated logic, broken links, old comments, inconsistent names, or confusing organization—but broad deletion would be risky.",
      "verification": "No confirmed low-risk cleanup remains, and existing behavior still passes. Every retained cleanup is supported by direct evidence, relevant builds and tests pass, the application still runs where applicable, unrelated work is untouched, and uncertain candidates are deferred rather than deleted.",
      "steps": [
        "Inspect the current code-project state and identify active branches, uncommitted edits, generated files, configuration, and other work that must not be disturbed.",
        "Collect possible cleanups, then use code references, configuration, documentation, tests, or runtime behavior to prove one candidate is genuinely low risk.",
        "Make the smallest useful change and run the existing build, tests, application checks, and diff review; keep it only when behavior stays intact and no unrelated work changes.",
        "Repeat until no confirmed low-risk cleanup remains, progress stalls, verification is unavailable, or the next candidate needs approval."
      ],
      "why": "One proven cleanup at a time keeps the work easy to review and undo. Requiring evidence before deletion—and protecting uncertain files and edits—prevents a tidy-up pass from removing code that is active but poorly understood.",
      "notes": "Here, repository means the code project and its files. This loop cleans source and project structure; the separate repository cleanup loop handles Git branches, pull requests, commits, and worktrees. Never delete something merely because its purpose is not immediately obvious.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/housekeeper-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "accessibility-repair-loop",
      "title": "Repair accessibility, highest-impact first",
      "url": "https://looprepo.dev/loops/accessibility-repair-loop",
      "loopType": "loop",
      "category": "quality",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "accessibility-audit",
        "accessibility-repair",
        "wcag-workflow",
        "inclusive-design-testing",
        "accessibility-regression"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Confirm barriers against an agreed standard, fix the one with the greatest user impact, and rerun the same checks.",
      "prompt": "Check [scope] against [accessibility standard, such as WCAG 2.2 AA] with automated scans and available keyboard, screen-reader, and other manual tests. Confirm each issue, rank it by harm, and fix the highest-impact blocker. Rerun the same checks, affected task, and regression tests. Keep only verified fixes. Stop when no blocker remains, progress stalls, verification is unavailable, or approval is required. Never silence a check or weaken the target. Return issues, fixes, evidence, exceptions, and untested needs.",
      "useWhen": "Use this when a website or app has a defined accessibility target and you can repeatedly test the relevant pages, components, or tasks for people using keyboards, screen readers, zoom, or other access methods.",
      "verification": "No confirmed accessibility barrier remains in the agreed pages, components, or user tasks. The same automated scans, available manual checks, affected user task, and regression tests pass after each retained fix without lowering the chosen accessibility standard.",
      "steps": [
        "Choose the pages, components, and user tasks to test; name the accessibility standard, such as WCAG 2.2 AA; and list the automated scans and manual checks that are actually available.",
        "Run the baseline, reproduce each finding instead of trusting a tool warning by itself, and rank confirmed barriers by the number of people affected and how severely they are blocked.",
        "Fix the most harmful barrier with the smallest underlying change, then repeat the same scan, manual check, user task, and relevant regression tests.",
        "Keep only verified fixes and repeat until no confirmed barrier remains or progress stalls, evidence cannot be collected, work is blocked, or approval is required."
      ],
      "why": "A fixed scope and repeated checks keep accessibility work tied to real people and reproducible evidence instead of an endless score chase. Fixing the most harmful confirmed barrier first directs effort to the users who are blocked most severely.",
      "notes": "Automated tools can find likely problems but cannot prove a product is accessible. Manual keyboard use, screen-reader checks, zoom, contrast review, and real user testing may still be needed. Record anything the available test setup could not cover.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/accessibility-repair-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "easy-onboarding-loop",
      "title": "Fix onboarding for a first-time user",
      "url": "https://looprepo.dev/loops/easy-onboarding-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "onboarding-improvement",
        "fresh-session-testing",
        "new-user-experience",
        "agent-friendly-onboarding",
        "onboarding-friction"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Start with no account or saved state, fix one confirmed onboarding obstacle, and retry the whole experience.",
      "prompt": "Act like a first-time user of [product]. Start at the real entry point in a clean session with no saved login, site data, remembered route, or hidden setup. Complete onboarding using only visible guidance and record obstacles. Fix the worst one with the smallest change that preserves every security, access, and product requirement. Discard the session and retry. Stop after one uninterrupted success, no safe fix, blocked access, or required approval. Return the path, changes, evidence, and blockers.",
      "useWhen": "Use this when new users may face unclear instructions, hidden assumptions, difficult recovery, or unnecessary steps that experienced users no longer notice because their accounts and browsers remember earlier setup.",
      "verification": "A first-time user can complete onboarding in one uninterrupted clean session. The full experience succeeds from the real starting point without saved browser state, secret setup, guessed routes, or manual repairs, and every real requirement remains intact.",
      "steps": [
        "Open a clean session with no saved login, cookies, site storage, remembered web address, secret setup, or repair left over from an earlier attempt.",
        "Begin where a real newcomer begins, complete the onboarding steps using only visible guidance, and record anything unclear, unexplained, unnecessarily difficult, or impossible to recover from.",
        "Fix the most harmful obstacle with the smallest change that preserves security, access, legal, onboarding, and product requirements.",
        "Throw away the session and retry the entire experience until one uninterrupted clean pass succeeds or no safe progress is possible, access is blocked, or approval is required."
      ],
      "why": "Saved logins and remembered setup hide problems from experienced users. Starting over after every fix shows whether the product itself now explains the path, while preserving real requirements prevents an easier experience from weakening security or access controls.",
      "notes": "A clean session means a new private browser or another isolated environment with no cookies, login, local storage, cache, or remembered route. Start where a newcomer would actually arrive and follow only the guidance the product exposes.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/easy-onboarding-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "pixel-safe-css-trim-loop",
      "title": "Delete dead CSS, pixel-safe",
      "url": "https://looprepo.dev/loops/pixel-safe-css-trim-loop",
      "loopType": "loop",
      "category": "design",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "css-cleanup",
        "pixel-safe-css",
        "visual-regression-testing",
        "dead-css-removal",
        "stylesheet-optimization"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Remove one unused or redundant style at a time and keep it gone only when every tested screen looks identical.",
      "prompt": "Reduce the CSS styling code [site] sends to users without changing tested screens. First capture representative pages, sizes, themes, and interactions, and record the built CSS size. Treat coverage reports only as suggestions. Remove one declaration or rule, rebuild, and rerun screenshots and project checks. Keep it only if every screenshot is pixel-identical and built CSS is smaller; otherwise revert. Stop when no supported candidate remains, progress stalls, or approval is required. Return reduction, evidence, and untested states.",
      "useWhen": "Use this when a website's styling files may contain unused declarations, duplicated rules, or old overrides and representative pages and interactions can be captured in repeatable screenshots.",
      "verification": "The delivered stylesheet is smaller while every tested screen remains pixel-identical. The same project checks and screenshots pass after each retained deletion, the built CSS file sent to users is smaller, and untested browsers, screens, or interactions remain explicit risks.",
      "steps": [
        "Before deleting styling code, list representative pages, screen sizes, light and dark modes, conditional content, hover and keyboard-focus states, and other important variants; capture screenshots and record the final built CSS size.",
        "Use a CSS coverage report to suggest declarations or rules that may be unused, then remove one candidate from the maintainable source file.",
        "Rebuild, run project checks, and recreate every screenshot; keep the deletion only when all images are pixel-identical and the built CSS is smaller, otherwise revert it.",
        "Repeat until no well-supported candidate remains, repeated attempts save nothing, the screenshots cannot cover the affected behavior, or approval is required."
      ],
      "why": "Screenshots taken before cleanup preserve the current appearance as the standard. Exact image comparison and one deletion per round catch visual changes that an automated coverage report cannot understand, including rules that matter only because of their order.",
      "notes": "CSS is the code that controls a page's appearance. A coverage report can suggest that a rule was not used during one visit, but it cannot prove the rule is unnecessary everywhere. Add uncertain browsers and interaction states before deleting their styles.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/pixel-safe-css-trim-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "cold-load-trimmer-loop",
      "title": "Trim what loads before first paint",
      "url": "https://looprepo.dev/loops/cold-load-trimmer-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "first-load-bytes",
        "bundle-size-optimization",
        "pixel-identical-screenshots",
        "lazy-loading",
        "web-performance-loop"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Reduce the data downloaded before the first screen appears, with tests and screenshots guarding behavior and appearance.",
      "prompt": "Reduce the data [web app] downloads before its first screen appears. First record passing tests, mobile and desktop screenshots, and compressed transferred bytes—the data actually downloaded. Use the build report only to suggest candidates. Defer, compress, or remove one item, then rebuild and rerun every check. Keep it only if tests pass, screenshots are pixel-identical, and bytes decrease; otherwise revert. Stop when no safe candidate remains, progress stalls, or approval is needed. Return measurements, changes, and untested states.",
      "useWhen": "Use this when a web app feels heavy on its first visit because it downloads too much code, styling, media, or other data before showing the initial screen.",
      "verification": "The first screen downloads less data without a tested behavior or pixel changing. The same production-like measurement reports fewer downloaded bytes, existing tests pass, every representative screenshot is pixel-identical, and uncertain dependency removal remains approval-gated.",
      "steps": [
        "Before changing code, record passing tests, representative mobile and desktop screenshots of the first screen, and a repeatable baseline for compressed transferred bytes—the amount actually downloaded.",
        "Use a build or bundle report to find large or early downloads, then choose one safe candidate to delay until needed, compress, inline, or remove.",
        "Rebuild and rerun the same tests, screenshots, and download measurement; keep the change only when every gate passes and bytes decrease, otherwise revert it completely.",
        "Repeat until no safe candidate remains, several attempts produce no improvement, the measurement is unreliable, or the next change needs approval."
      ],
      "why": "Recording behavior and screenshots before the first change prevents a broken screen from becoming the new normal. One download change per round also makes it clear which edit saved bytes and makes a failed attempt easy to undo.",
      "notes": "Measure compressed transferred bytes—the amount sent over the network—not the larger source files developers read. Screenshots protect only the states they capture, so include logged-out, logged-in, empty, error, or other relevant first screens before trusting a risky change.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/cold-load-trimmer-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "ui-ux-score-loop",
      "title": "Score every screen on a real task",
      "url": "https://looprepo.dev/loops/ui-ux-score-loop",
      "loopType": "goal",
      "category": "design",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ui-ux-score",
        "browser-flow-audit",
        "responsive-design-review",
        "fresh-browser-state",
        "user-experience-improvement"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Complete a real user task, score each meaningful screen with one checklist, fix the weak spots, and retest end to end.",
      "prompt": "Improve [user flow, such as signup] at [URL] until [completion criterion]. In a real browser, start each pass from fresh state—no saved login, cookies, or site data. Capture meaningful screens at the agreed sizes and modes, score them with one checklist, and improve the weakest safe area. Rerun the whole flow and keep only regression-free changes. Stop on success, two full passes with no gain, blocked access, or required approval. Return scores, screenshots, changes, and stop reason.",
      "useWhen": "Use this for a real task such as signup, login, onboarding, checkout, sharing, or creating and editing an item when the entire experience can be exercised in a browser and scored consistently.",
      "verification": "The complete user task scores better without making another important screen worse. The final dashboard shows the same entry point, fresh browser state, screen sizes, modes, scoring rubric, screenshots, score changes, and stop reason for every retained improvement.",
      "steps": [
        "Choose the user task, starting URL, success target, browser, clean-session rule, screen sizes, light or dark modes, screens to capture, and anything the agent must not change.",
        "Complete the task once without editing; capture normal screens plus meaningful loading, error, recovery, and success states, then score each with the same user-focused rubric.",
        "Improve the weakest safe area, start a new clean browser session, and repeat the entire task under the same conditions so before-and-after scores are comparable.",
        "Keep only changes that improve the target without hurting another important screen; stop on success, two passes with no gain, blocked access, or required approval."
      ],
      "why": "A clean browser session exposes problems that saved logins, cookies, and remembered settings can hide. Repeating the same task with the same scoring rubric makes the result comparable instead of relying on a vague impression that the interface feels better.",
      "notes": "A flow means a user goal, such as signing up or checking out—not a guessed web address. A screen size is sometimes called a viewport; a mode may be light or dark. Judge what the user can see and do, not hidden console output.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/ui-ux-score-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "goal-forge-loop",
      "title": "Interview, then write SPEC and GOAL",
      "url": "https://looprepo.dev/loops/goal-forge-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "goal-forge",
        "codex-goal-planning",
        "spec-md",
        "goal-md",
        "autonomous-coding-contract"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Interview the user, capture what to build in SPEC.md, and how the agent should execute and verify it in GOAL.md.",
      "prompt": "Turn [rough coding idea] into two planning files before Codex starts /goal, its long-running task mode. Interview the user, then write SPEC.md: what to build, exclude, and consider, plus measurable done_when completion checks. Write GOAL.md: the work plan, progress scorecard, quick and final checks, memory files, evidence, and approval boundaries. If any key decision, permission, tool, environment requirement, or test is missing, stop as not ready. Do not start implementation without approval.",
      "useWhen": "Use this when a rough coding idea is too vague to hand to Codex for a long autonomous run and the user first needs to settle scope, completion checks, safety boundaries, and required tools.",
      "verification": "The planning files say what to build, how to judge it, and when to stop. Every done_when completion check names observable evidence, the quick and final checks can actually run, the environment is ready, and unresolved decisions are clearly marked not ready.",
      "steps": [
        "Ask the user what the finished feature should do, what is out of scope, which edge cases matter, what could go wrong, and what evidence would prove completion; write those decisions in SPEC.md.",
        "Point out ambiguous requirements with concrete interpretations and have the user resolve product decisions instead of letting the coding agent silently choose.",
        "Write GOAL.md with the ordered work, a progress scorecard, quick checks for each iteration, slower final checks, memory files for long runs, approval boundaries, and required evidence.",
        "Confirm that the tools, permissions, environment, and tests exist; stop as not ready when anything essential is missing, and start the long-running task only after approval."
      ],
      "why": "Goal Forge makes the user decide what success means before an agent spends hours coding. The two files give Codex a stable target, repeatable checks, memory across a long run, and an honest not-ready state when important information is missing.",
      "notes": "In the source workflow, /goal is Codex's long-running task mode. SPEC.md describes the product decision; GOAL.md tells Codex how to execute and verify it; PLAN.md, ATTEMPTS.md, and NOTES.md preserve progress and learning across the run.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/goal-forge-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "multi-llm-convergence-loop",
      "title": "Two models must agree",
      "url": "https://looprepo.dev/loops/multi-llm-convergence-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "multi-llm-review",
        "cross-model-consensus",
        "artifact-convergence",
        "alternating-reviewers",
        "independent-ai-review"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Alternate two models from different providers to review a plan, doc, or diff until both approve the exact same version.",
      "prompt": "Review [plan, specification, document, or code change] against [quality bar] for at most [pass limit] rounds. Have one of two genuinely different model families—AI systems from separate providers—review it. Verify each finding and apply only necessary fixes, then give the revised version to the other reviewer. Succeed only when both approve the same unchanged version. Stop at the limit, repeating disagreement (oscillation), unavailable review, or required approval. Return the final work, round log, verdict, and disagreements.",
      "useWhen": "Use this when an important plan, specification, design, document, or code change benefits from two independent AI perspectives rather than one model reviewing its own blind spots.",
      "verification": "Two different AI model families approve the exact same version. The final two clean reviews come from different model families with no edit between them; a pass limit, repeating disagreement, unavailable reviewer, or approval boundary is reported as a stall instead of consensus.",
      "steps": [
        "Choose the work being reviewed, define what counts as acceptable, set a maximum number of rounds, and gather the source material reviewers should trust.",
        "Give the current version to the first AI model family, check whether each finding is valid, apply only necessary fixes, and record the round.",
        "Give the resulting version to the other model family; if either reviewer causes another edit, both must review the new version again.",
        "Finish only when both independently approve one unchanged version; otherwise stop at the round limit, repeated back-and-forth, reviewer failure, or an approval boundary."
      ],
      "why": "Different model families can notice different problems. Requiring both to approve the exact same version prevents a clean review of an older draft from being counted as approval of a newer one, and the round log shows how the agreement was reached.",
      "notes": "A model family means a genuinely separate model lineage, such as a Codex/OpenAI reviewer and a Claude/Anthropic reviewer—not two prompts sent to the same underlying model. With only one family, label the result a single-model review and do not claim consensus.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/multi-llm-convergence-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "propagation-compliance-loop",
      "title": "Propagate a value everywhere it lives",
      "url": "https://looprepo.dev/loops/propagation-compliance-loop",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "configuration-propagation",
        "version-update-audit",
        "stale-value-search",
        "repository-consistency",
        "grep-verification-loop"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Update every copy of a changed value across the project, hunt down leftovers, and prove only intentional old references remain.",
      "prompt": "After changing a version, count, rule, name, or configuration, list where the new value belongs and update it. Search the project for the old value and related forms. Review each match: fix real stale values, but keep intentional history, examples, migrations, or compatibility rules. Repeat until zero stale values remain. If one returns for two rounds, stop and identify what may be regenerating it. Return changes, intentional matches, and search output.",
      "useWhen": "Use this after changing something that appears in several files—such as a version number, feature name, count, rule, setting, or identifier—and every copy must stay consistent.",
      "verification": "No unintended copy of the old value remains. The final searches find only references that are intentionally historical or required for examples, migrations, or compatibility, with a reason recorded for each one.",
      "steps": [
        "List the files, documentation, settings, generated outputs, or operational notes that are expected to copy the changed value.",
        "Update the known copies, then search the whole project for the old value, old spelling, and other likely leftover forms.",
        "Decide whether each match is truly stale or intentionally preserved history, an example, a migration, or a compatibility rule; fix only the stale matches.",
        "Repeat the same searches until no stale match remains; if one comes back for two rounds, stop and identify the generator or process restoring it."
      ],
      "why": "The repeat search is the important part: it catches copies missed by the first update. Reviewing each match also prevents a broad replacement from corrupting historical notes, migration code, or examples that intentionally show the old value.",
      "notes": "The exact files depend on the change. The original submission used several operational notes and procedure files; another project might need code, tests, documentation, deployment settings, generated files, or all of them.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/propagation-compliance-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "promise-to-proof-loop",
      "title": "Make your claims match reality",
      "url": "https://looprepo.dev/loops/promise-to-proof-loop",
      "loopType": "goal",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "product-promise-audit",
        "customer-trust",
        "claim-verification",
        "evidence-based-product-review",
        "marketing-product-alignment"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Compare claims in marketing, docs, demos, and AI answers against current evidence, then fix or narrow anything unsupported.",
      "prompt": "List every customer-facing promise [product] makes in marketing, documentation, demos, and AI answers. Compare each promise with current product behavior and evidence, then label it proven, partly proven, misleading, unsupported, outdated, or missing evidence. Fix or narrow the riskiest mismatch and rerun the affected check. Repeat until no high-risk unsupported promise remains. Ask before changing production or public copy. Return the promises, evidence, fixes, and decisions needed.",
      "useWhen": "Use this when what a product says it does may no longer match what it actually does across marketing, documentation, demos, support answers, or the live product.",
      "verification": "Every high-risk customer promise is supported, narrowed, or waiting on an explicit decision. Each promise links to current evidence, and every high-risk mismatch is fixed, narrowed to what the product can prove, or clearly approval-gated.",
      "steps": [
        "List the promises customers can see and rewrite each one as a concrete expectation, such as a feature working, a limit being honored, or an answer being accurate.",
        "Compare each expectation with current product behavior, code, tests, documentation, examples, logs, or other direct evidence; do not guess.",
        "Rank mismatches by the harm they could do to customer trust, then fix the riskiest one or narrow the public promise to what the product can prove.",
        "Rerun the same check and repeat until no high-risk unsupported promise remains, progress is blocked, or the next action needs approval."
      ],
      "why": "This turns a vague question—can customers trust what we say?—into a list of promises that can each be checked. Fixing one risky mismatch at a time keeps the product and its public explanation aligned without turning the audit into an uncontrolled rewrite.",
      "notes": "Evidence can include live product behavior, tests, documentation, logs, screenshots, or reproducible examples. A promise may be supported, narrowed, or removed; the product does not always need to change. Production changes and public publication still require approval.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/promise-to-proof-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "recent-feedback-sweep",
      "title": "Turn recent complaints into fixes",
      "url": "https://looprepo.dev/loops/recent-feedback-sweep",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "recent-user-feedback",
        "project-wide-issue-audit",
        "failure-pattern-sweep",
        "regression-prevention",
        "ai-coding-agent"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Convert recent user-reported problems into reusable failure patterns, fix every confirmed match, and verify a clean final pass.",
      "prompt": "Review all available threads from [lookback window] where I reported something wrong with [project] and asked for a fix. Build a deduplicated issue list, group it into failure patterns, and verify current state. Audit the complete project for every pattern, fix each confirmed instance, and add regression coverage where practical. Repeat the full audit until it finds no remaining instance or [iteration budget] ends. Stop on blocked or approval-gated work. Return the issues, fixes, evidence, and blockers.",
      "useWhen": "Use this after several days of project feedback when repeated mistakes may point to similar issues elsewhere and the agent can inspect both the conversation history and the complete current project.",
      "verification": "The issue inventory is closed and a fresh pattern audit is clean. Every reported issue and newly found match has current proof of resolution; blocked, approval-gated, or budget-exhausted items remain explicitly open.",
      "steps": [
        "Define the lookback window and complete project surface, then collect every accessible thread in which the user reported a problem and requested a fix.",
        "Deduplicate the reported issues, verify their current status, and turn the concrete examples into explicit failure patterns and audit checks.",
        "Audit every in-scope project surface for each pattern, fix one confirmed instance at a time, and add regression coverage where practical.",
        "Run targeted checks after each fix, then rerun the complete pattern audit and relevant full checks before declaring the sweep clean."
      ],
      "why": "Recent corrections are concrete examples of the quality bar the project missed. Grouping them into failure patterns turns one-off feedback into a reusable audit rubric, while a fresh full sweep catches sibling defects and verifies the current project rather than trusting old thread state.",
      "notes": "Thread access and a complete surface inventory are prerequisites. Do not infer defects from neutral discussion, reopen resolved issues without checking current behavior, or claim success while an inaccessible, blocked, approval-gated, or budget-exhausted item remains. Get approval before destructive, production, or external actions.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/recent-feedback-sweep/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "five-minute-repository-maintainer-loop",
      "title": "Triage a repo in five minutes",
      "url": "https://looprepo.dev/loops/five-minute-repository-maintainer-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "codex-repository-maintenance",
        "multi-repository-orchestration",
        "five-minute-agent-loop",
        "github-project-triage",
        "thread-delegation"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Triage the repo, route bounded maintenance to dedicated threads, and require proof and permission before anything lands.",
      "prompt": "While repository maintenance is active, wake every five minutes. Triage [repositories] and read each repository thread's latest state. Reuse one thread per repository; assign its highest-value bounded task only within granted permissions, and do not interrupt coherent active work. Require tests, live proof, autoreview, and green CI before work can land. Escalate product, access, security, or irreversible decisions. Record meaningful changes and stop when every item is landed, decision-ready, blocked, or has no work.",
      "useWhen": "Use this when Codex may coordinate maintenance across several active repositories and you want parallel work to stay steerable without duplicating or micromanaging threads.",
      "verification": "Every repository item reaches a proven handoff or terminal state. Authorized autonomous work lands with evidence; other items are decision-ready, blocked with one exact ask, or recorded as a clean no-op.",
      "steps": [
        "Define the repository scope, exclusions, and separate permissions for triage, delegation, implementation, push, CI repair, merge, and release.",
        "Every five minutes, refresh each repository queue and read the latest state of its existing thread before choosing the highest-value eligible item.",
        "Reuse one thread per repository, assign one bounded task, and let coherent active work continue unless it is blocked, stalled, unsafe, or off course.",
        "Require tests, live proof, autoreview, and green CI; record the evidence, then route the next item or present the owner with one exact decision."
      ],
      "why": "A five-minute heartbeat keeps the control plane current without turning polling into micromanagement. One thread per repository preserves context, while proof and authorization gates make autonomous landing auditable.",
      "notes": "The source pairs Maintainer Orchestrator with github-project-triage, autoreview, and computer use for live proof. A heartbeat automates observation, not authority: triage, delegation, implementation, push, merge, and release remain separate permissions. Read current thread state before steering, and never duplicate or interrupt active work.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/five-minute-repository-maintainer-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "revolve-self-improvement-loop",
      "title": "Improve via checkpointed experiments",
      "url": "https://looprepo.dev/loops/revolve-self-improvement-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "revolve",
        "agent-self-improvement",
        "checkpoint-evaluation",
        "revisioned-experiments",
        "evidence-based-promotion"
      ],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Improve prompts, code, or config through checkpointed experiments whose scores stay comparable across sessions.",
      "prompt": "Use Revolve to improve a support prompt, code path, or testable subject. In revolve/, define the goal and [budget], freeze the tests and scoring, checkpoint the current version, and record a baseline. Each round, test one hypothesis; keep only a clear, regression-free win. If the evaluation changes, open a new revision and rerun the baseline. Ask before changing live files. Stop on success, no progress, a blocker, or exhausted budget. Return the best checkpoint, comparisons, rollback, and next action.",
      "useWhen": "Use Revolve to improve a prompt, policy, workflow, model configuration, code path, or dataset when experiments must remain comparable and resumable across sessions.",
      "verification": "The best Revolve checkpoint wins within one evaluation revision. The incumbent and candidates have comparable recorded runs, accepted changes pass every guard, rollback is available, and live promotion has approval.",
      "steps": [
        "Create or resume revolve/, define the objective and permissions, freeze an evaluation revision, checkpoint the incumbent, and record its baseline.",
        "Choose one evidence-backed hypothesis, create a candidate checkpoint, and test it under the unchanged revision.",
        "Promote internally only on a meaningful guard-safe win; if the evaluation changes, open a new revision and rerun the incumbent.",
        "Stop on a named condition, and require explicit approval plus verification before changing live files."
      ],
      "why": "Revolve's revision boundaries prevent scores from different tests or rubrics from being compared as equivalent. Checkpoints and an internal-before-live promotion boundary keep long-running research resumable and reversible.",
      "notes": "The source examples include improving CLI error messages, reducing image-export latency, tuning a support-assistant prompt, and hardening a parser. Replace the subject and metric, but keep the revision, checkpoint, and rollback discipline.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/revolve-self-improvement-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "codex-completion-contract-loop",
      "title": "Define done before Codex starts",
      "url": "https://looprepo.dev/loops/codex-completion-contract-loop",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "codex-goal",
        "completion-contract",
        "evidence-audit",
        "definition-of-done",
        "false-completion-prevention"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Set the completion contract up front, track proof for every requirement, and block partial work from being called done.",
      "prompt": "Run $goal-planner-codex [task] for long-running Codex work where partial work could be mistaken for done. Landing a PR and verifying production is one example. Before acting, define every required outcome and its evidence. After each bounded action, mark requirements proved, weak, missing, or contradicted. Complete the Goal only when all are proved; otherwise stop as blocked, stalled, or exhausted. Ask before creating Goal state. Finish with the requirement-to-evidence table, status, owner, and next action.",
      "useWhen": "Use this for long-running Codex work, pull requests, runtime checks, or user-visible artifacts where a plausible partial result could be mistaken for completion.",
      "verification": "Every Codex Goal requirement has current, adequate proof. The final audit contains no weak, missing, or contradicted required item; otherwise the work remains open, blocked, or exhausted.",
      "steps": [
        "Recover a measurable definition of done for every ambiguous requirement.",
        "Record the requirements, scope, non-goals, evidence plan, and current status without expanding the requested work.",
        "Execute one bounded action at a time and attach current evidence to each affected requirement.",
        "Audit every requirement before closure and preserve honest blocked, exhausted, stalled, or contradicted states."
      ],
      "why": "A durable completion contract keeps the definition of done visible across long sessions. Mapping every requirement to evidence makes false completion easy to detect.",
      "notes": "Use $goal-planner-codex only when the user explicitly asks for a Codex Goal or completion audit. Create native Goal state only with approval; ordinary task planning does not need it, and budget exhaustion never counts as success.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/codex-completion-contract-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "autonomy-loop",
      "title": "Builder vs. reviewer, proving each test",
      "url": "https://looprepo.dev/loops/autonomy-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "autonomy-loop",
        "adversarial-code-review",
        "mutation-testing",
        "builder-reviewer-workflow",
        "claude-code-loop"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "A builder and an adversarial reviewer pass a git baton between worktrees, proving every new test can catch its fix.",
      "prompt": "Use autonomy-loop for [repository task] after the test, build, and lint gates pass. Run /autonomy-loop:autonomy-init, then start builder and reviewer in separate worktrees. The builder reads LOOP-STATE.md, makes one bounded change, and adds a red-before, green-after test. The reviewer reruns the gates and proves the test by reverting or mutating the fix. Accept only on both passes; park protected or repeated-failure work for a human. Finish with the commit, gate evidence, test proof, trust tier, and risks.",
      "useWhen": "Use autonomy-loop when a repository has deterministic test, build, and lint gates plus a task suited to repeated builder-reviewer handoffs.",
      "verification": "Every accepted wave passes autonomy-loop's proof-of-test gate. The new test fails without the change, passes with it, every configured gate passes, and protected production changes remain human-gated.",
      "steps": [
        "Initialize autonomy-loop, configure deterministic gates and protected paths, and create separate builder and reviewer worktrees.",
        "Have the builder read LOOP-STATE.md, implement one bounded change, add a red-before, green-after test, and hand off.",
        "Have the reviewer rerun every gate and use revert-or-mutate proof to show the test catches the change.",
        "Accept only on both passes; otherwise return findings or park the wave for a human when a circuit breaker fires."
      ],
      "why": "Separate worktrees and a git-backed LOOP-STATE.md baton keep the roles independent and resumable. The revert-or-mutate check catches tests that execute code without proving the fix.",
      "notes": "The source implementation uses autonomy-loop commands, separate worktrees, and a git-backed baton. Treat local hooks as tripwires, not a security boundary, and keep protected changes behind enforced approval.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/autonomy-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "infinite-clickbait-loop",
      "title": "Design a thumbnail that earns clicks",
      "url": "https://looprepo.dev/loops/infinite-clickbait-loop",
      "loopType": "goal",
      "category": "design",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "infinite-clickbait",
        "youtube-thumbnail-loop",
        "thumbnail-iteration-workflow",
        "clickbait-scoring-rubric",
        "ai-visual-design"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Generate ten concepts, score the top three against a real channel, and sharpen the winner without misleading viewers.",
      "prompt": "For [video], use [approved assets] to make ten thumbnail concepts. Score each at real YouTube sizes against [inspiration channel] for clarity, curiosity, emotional pull, contrast, and accuracy. Take the top three, improve each one's weakest dimension, and rescore them under the same rubric. Keep iterating the strongest concept until it clears [quality threshold] or [budget] ends. Reject anything the video cannot deliver. Return the winner, two runners-up, previews, final scores, and rationale.",
      "useWhen": "Use this when a video topic and asset set are ready but the thumbnail needs several structured ideation and critique rounds before production.",
      "verification": "One accurate thumbnail clears the fixed quality threshold. The winner outscores the alternatives under the same conditions, remains legible at realistic sizes, and represents the video accurately.",
      "steps": [
        "Define the video subject, approved assets, inspiration channel, quality threshold, budget, and five-part rubric.",
        "Create ten distinct concepts, inspect them at real YouTube sizes, and score each one under the same conditions.",
        "Select the top three, improve the weakest dimension of each, and rescore them.",
        "Stop at the quality bar or budget, reject misleading concepts, and return the winner plus two runners-up."
      ],
      "why": "A varied first set creates real options, while a fixed rubric makes later rounds comparable. Scoring accuracy prevents curiosity from becoming a promise the video cannot keep.",
      "notes": "Choose an inspiration channel whose audience and visual language are relevant. Evaluate the actual thumbnail crop at desktop and mobile sizes, and reject concepts that misrepresent the video's substance.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/infinite-clickbait-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "fresh-clone-loop",
      "title": "Make onboarding work from zero",
      "url": "https://looprepo.dev/loops/fresh-clone-loop",
      "loopType": "goal",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "fresh-clone-loop",
        "readme-verification",
        "developer-onboarding-test",
        "clean-environment-setup",
        "repository-documentation-workflow"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Follow the README in a throwaway environment, fix every hidden setup assumption, and restart until a clean clone just works.",
      "prompt": "Clone [repository] into a disposable environment and follow only its README to the documented ready state, such as running the app or building the package. When a step fails or assumes missing knowledge, record the gap, fix the setup or documentation issue, discard the environment, and start again. Carry no dependencies, configuration, credentials, or repairs between attempts. Stop when one uninterrupted fresh clone reaches that state, progress stalls, or [budget] ends. Return exact commands, gaps closed, and remaining blockers.",
      "useWhen": "Use this to test whether a repository's onboarding instructions work in a clean environment without undocumented help.",
      "verification": "A clean environment reaches the documented ready state using only the README. The final run uses only the onboarding guide and needs no unstated dependency, configuration, or manual repair.",
      "steps": [
        "Create a disposable environment with no project dependencies or configuration carried over from another checkout.",
        "Fresh-clone the repository and follow only the README, recording every missing step, hidden assumption, and failure.",
        "Fix the smallest setup or documentation gap, discard the environment completely, and begin again.",
        "Repeat until one clean run reaches the documented ready state without intervention, then report the exact commands and gaps closed."
      ],
      "why": "Destroying the environment after each repair prevents local state from hiding the next problem. The final uninterrupted run is direct evidence that the README, not the operator's memory, is sufficient.",
      "notes": "Use an isolated disposable environment and review the repository before executing it. Never copy personal credentials into the test environment or run untrusted setup scripts on a production host.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/fresh-clone-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "devils-advocate-design-loop",
      "title": "Attack a design until it holds",
      "url": "https://looprepo.dev/loops/devils-advocate-design-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "devil-s-advocate-loop",
        "adversarial-design-review",
        "critic-builder-workflow",
        "architecture-objection-log",
        "red-team-design-process"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "A critic hammers the design and a builder answers — every objection tracked, and none closed without evidence.",
      "prompt": "Before committing to an architecture, interface, or rollout plan, have a critic argue that it is wrong. Record each objection, impact, and status in a repository-local log at .agent-reviews/redteam.md. The builder must fix and verify each high-impact weakness or document why it is accepted; the critic may reopen unsupported answers. Stop when no high-impact objection remains or the same issues repeat for two rounds without new evidence. Finish with the decision, resolved and accepted objections, evidence, and any stalemate.",
      "useWhen": "Use this before committing to an architecture, interface, rollout plan, or other consequential design that benefits from structured adversarial review.",
      "verification": "No high-impact objection remains open. Every logged objection is verified as resolved or explicitly accepted with evidence, or the final report truthfully records a two-round stalemate.",
      "steps": [
        "Write the design goals and acceptance criteria, then initialize .agent-reviews/redteam.md inside the repository and keep it out of commits.",
        "Have the critic present the strongest evidence-backed case against the current design and rank each objection by impact.",
        "Have the builder repair the weakness or document an explicit acceptance rationale, then verify the result against the stated criteria.",
        "Let the critic reopen weak answers and repeat until the objections are closed with evidence or the loop reports a stalemate honestly."
      ],
      "why": "Separating critic and builder roles makes disagreement explicit. A persistent objection log prevents circular debate, while evidence-based closure stops the builder from declaring success by explanation alone.",
      "notes": "Keep the critic independent where possible. Do not change the acceptance criteria mid-run simply to close a difficult objection.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/devils-advocate-design-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "self-improving-champion-loop",
      "title": "Promote prompts only on holdout wins",
      "url": "https://looprepo.dev/loops/self-improving-champion-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "self-improving-loop",
        "champion-challenger-evaluation",
        "goodhart-prevention",
        "independent-evaluation-gate",
        "bounded-optimization-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Test challenger prompts on a working set, promote only on fresh holdout wins, and keep the champion when results are uncertain.",
      "prompt": "Improve a prompt, policy, or configuration. A support assistant's system prompt is one example. Save the champion, its score, a working set, untouched holdout cases, must-pass checks, and [budget]. Each round, change one thing based on a recorded failure. Promote the challenger only if it beats the champion on holdouts by [margin] without weakening a must-pass check; otherwise keep the champion. Stop at the target, budget limit, or no progress. Return the winner, scores, experiment log, and remaining failures.",
      "useWhen": "Use this to tune a prompt, policy, or configuration when cheap iteration is useful but final acceptance must use fresh examples.",
      "verification": "The best holdout-tested champion is returned. Every challenger is logged, and accepted changes beat the previous champion on untouched cases without weakening a must-pass check.",
      "steps": [
        "Save the current champion, working set, untouched holdout cases, must-pass checks, improvement margin, budget, and experiment log.",
        "Use a recorded failure to propose one targeted challenger and test it on the working set.",
        "Freeze promising challengers and evaluate them on the untouched holdout cases and every must-pass check.",
        "Promote only a meaningful, regression-free holdout win; log every result and return the champion at the stop condition."
      ],
      "why": "Separating the working set from fresh holdout cases limits overfitting. Keeping the current best by default prevents regressions, while a fixed budget bounds the search.",
      "notes": "Keep the working set and holdout cases separate: edit against the former, judge final acceptance on the latter. Choose the budget and margin before starting, and do not weaken a must-pass check after a failed challenger.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/self-improving-champion-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "war-loops-frontend-designer",
      "title": "Rebuild a page pixel-for-pixel",
      "url": "https://looprepo.dev/loops/war-loops-frontend-designer",
      "loopType": "loop",
      "category": "design",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "war-loops",
        "autonomous-frontend-designer",
        "frontend-fidelity",
        "visual-evaluation-loop",
        "responsive-motion-matching"
      ],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Capture a real page, build a static mirror and a live version, then repair the weakest fidelity signals until they match.",
      "prompt": "Point War Loops at an authorized URL or image. Capture it with a genuine browser and record the layout, styles, content, motion, and responsive behavior. Build a static Pencil mirror and a moving Forge version. Compare both with the source at desktop, tablet, and mobile sizes; repair only the weakest fidelity signals. Stop when every gate passes, progress stalls, or capture is blocked. Finish with the builds, spec, renders, scores, and remaining gaps.",
      "useWhen": "Use War Loops when an authorized interface must be rebuilt from a URL or image and judged on appearance, motion, and responsive behavior.",
      "verification": "The builds match the source across all three fidelity axes. Static appearance, experiential motion, and responsive reflow pass their gates, or the run reports stagnation or a blocked capture.",
      "steps": [
        "Capture the source with a genuine browser and extract its design spec, motion, and target viewports.",
        "Build the static Pencil mirror and moving Forge version from the verified spec.",
        "Judge both across static design, experiential motion, and responsive reflow.",
        "Repair the weakest signals without rebuilding what already matches, then repeat to a terminal fidelity decision."
      ],
      "why": "War Loops separates a page's still appearance from how it moves and reflows. Its surgical critic targets the weakest measured signals without churning areas that already match.",
      "notes": "The source implementation uses War Loops with Pencil and Forge. Confirm authorization to reproduce the reference, and stop on a bot wall, login gate, or unreliable capture.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/war-loops-frontend-designer/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "boeing-747-benchmark",
      "title": "The Boeing 747 vision benchmark",
      "url": "https://looprepo.dev/loops/boeing-747-benchmark",
      "loopType": "loop",
      "category": "design",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "boeing-747-benchmark",
        "three-js-agent-workflow",
        "vision-self-verification",
        "3d-reconstruction-loop",
        "camera-inspection-system"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "An agent builds a 747 from Three.js primitives, renders nine fixed angles, and fixes whatever each view exposes.",
      "prompt": "Before building, choose reference images, a scoring rubric, [visual threshold], and [budget]. Build the most realistic Boeing 747 you can from Three.js primitives, then create a rig that screenshots nine repeatable angles. After each change, render and score the same views, have a critic identify the weakest feature, and fix it without regressing stronger views. Keep the best version. Stop at the threshold, stalled progress, or budget. Finish with the model, nine renders, scores, remaining gaps, and run summary.",
      "useWhen": "Use this as a concrete Three.js vision benchmark, or adapt the same capture-and-critic pattern to another rendered subject.",
      "verification": "The Boeing 747 meets the visual bar from all nine angles. The same camera rig and rubric show every required view meeting the preset threshold, or the run reports stagnation, budget exhaustion, and remaining gaps.",
      "steps": [
        "Choose reference images, a scoring rubric, a visual threshold, and a budget; then build the first Boeing 747 from Three.js primitives.",
        "Create a repeatable rig that renders the same nine angles after every meaningful change.",
        "Score each view against the references, have a critic identify the weakest feature, and fix it without losing stronger work.",
        "Keep the best version and repeat until all nine views clear the visual bar or another named stop is reached."
      ],
      "why": "The nine-angle rig turns a subjective 3D build into a repeatable visual test. Critiquing the same views after each change exposes problems that one hero render can hide.",
      "notes": "The source run used a Boeing 747, Three.js primitives, nine camera angles, and repeated critics. To adapt it, replace the subject and renderer but keep fixed views, a visible quality bar, and preserved comparison renders.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/boeing-747-benchmark/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "loop-harness-verification-loop",
      "title": "Verify agent output before it ships",
      "url": "https://looprepo.dev/loops/loop-harness-verification-loop",
      "loopType": "loop",
      "category": "git",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "loop-harness",
        "scheduled-coding-agent",
        "git-worktree-isolation",
        "second-agent-verification",
        "autonomous-agent-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Run one agent in an isolated worktree and release its staged output only after a second agent verifies the work.",
      "prompt": "Use Loop Harness for scheduled repository work such as CI triage, issue grooming, dependency updates, or docs sync. Set [retry limit], then start an isolated git worktree. Let one Claude session stage a patch or outbox message and a second Claude session verify it against explicit criteria. Ship only after a pass; otherwise preserve the findings and retry only within the limit. Finish with the source revision, staged output, verifier result, delivery status, and next run.",
      "useWhen": "Use this when a recurring repository task should run unattended but one agent must not be allowed to generate and approve the same output.",
      "verification": "Only independently verified output ships. A second-agent pass releases the configured output; a failed verification preserves evidence and produces no external change.",
      "steps": [
        "Set the retry limit, wake the due Loop Harness task, and create an isolated worktree from the approved source revision.",
        "Have the primary Claude session stage one bounded result without publishing it.",
        "Have a second Claude session inspect the staged work against explicit acceptance criteria.",
        "Ship on a pass; otherwise preserve the findings, publish nothing, and retry only until the preset limit."
      ],
      "why": "Workspace isolation limits interference, and the second-agent gate separates generation from approval. The result can run repeatedly without relying on one session's confidence.",
      "notes": "The source implementation uses Loop Harness, git worktrees, and separate model sessions. Start with read-only tasks, test one run first, cap runtime and retries, and grant only the tools each agent needs.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/loop-harness-verification-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "clodex-adversarial-review-loop",
      "title": "Claude ships, Codex reviews",
      "url": "https://looprepo.dev/loops/clodex-adversarial-review-loop",
      "loopType": "loop",
      "category": "review",
      "difficulty": "advanced",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "clodex",
        "codex-adversarial-review",
        "claude-code-plugin",
        "review-fix-loop",
        "pull-request-automation"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Open a PR, run an independent Codex review, fix every blocking finding, and repeat until it's clean.",
      "prompt": "Run /clodex [task] think hard --max-iter 5 --threshold medium. Claude plans the task, implements it, opens a pull request, asks Codex for an adversarial review, fixes findings above the accepted severity, and repeats. Keep the branch, PR, findings, verdict, and iteration state resumable. Stop when Codex approves, only accepted findings remain, progress stalls, or the iteration cap is reached. Never describe an errored or exhausted run as approved. Finish with the PR, checks, verdict, and remaining findings.",
      "useWhen": "Use Clodex when Claude is building a meaningful code change and Codex should independently review each repair round.",
      "verification": "The pull request reaches the configured review bar. Codex approves it or only explicitly accepted findings remain; errors, stalls, and exhausted limits are reported as such.",
      "steps": [
        "Choose the task, thinking level, maximum iterations, and highest acceptable finding severity.",
        "Have Claude plan, implement, verify, and open the pull request through Clodex.",
        "Run the Codex adversarial review, fix blocking findings, push, and review again.",
        "Persist state across rounds and finish with the verdict, remaining findings, checks, and pull-request link."
      ],
      "why": "Clodex separates the Claude builder from the Codex reviewer and turns review feedback into a bounded repair loop. Persisted state keeps the work resumable without treating an interruption as approval.",
      "notes": "The source implementation uses Clodex with Codex as the adversarial reviewer. Treat the severity threshold as a ceiling for acceptable findings, not a minimum severity to inspect.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/clodex-adversarial-review-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "product-update-podcast-loop",
      "title": "Turn product changes into a podcast",
      "url": "https://looprepo.dev/loops/product-update-podcast-loop",
      "loopType": "loop",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-podcast-workflow",
        "product-update-podcast",
        "jellypod-mcp",
        "release-communication",
        "editorial-automation"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Each cycle, turn meaningful public product changes into a short, source-grounded podcast episode.",
      "prompt": "Each night, review publicly released product changes and select only those users need to know. Verify each against the product, docs, or release notes. Use the Jellypod MCP to turn the approved changes into a three-to-five-minute podcast explaining what changed, why it matters, and how to try it. Check the script and audio for accuracy, clarity, and pronunciation. If nothing meaningful shipped, make no episode. Ask before publishing. Finish with the draft episode, sources, and review result.",
      "useWhen": "Use this when a product ships frequently enough that users would benefit from a short recurring audio explanation of what changed and how to use it.",
      "verification": "The episode accurately covers every meaningful public update. Finish with a review-ready three-to-five-minute episode, or a confirmed no-episode result when nothing meaningful shipped.",
      "steps": [
        "Collect the previous day's public product changes, documentation, and release notes.",
        "Select the changes most meaningful to users and verify what actually shipped.",
        "Use Jellypod to draft a three-to-five-minute episode covering the benefit and how to try each selected change.",
        "Review the script and audio against the sources, regenerate weak passages, and request approval before publishing."
      ],
      "why": "A fixed release window keeps coverage current, while editorial selection and source verification prevent the episode from becoming an automated reading of commit titles.",
      "notes": "Use only publicly released information. Do not expose private repository context, customer data, security-sensitive details, or unreleased work in the generated episode.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/product-update-podcast-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "customer-ai-deployment-loop",
      "title": "Ship one customer AI priority",
      "url": "https://looprepo.dev/loops/customer-ai-deployment-loop",
      "loopType": "goal",
      "category": "devops",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "customer-ai-deployment",
        "ai-workflow-rollout",
        "approval-gates",
        "production-monitoring",
        "ai-roi"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Advance a single customer priority into a validated, gradually released system with monitoring, approvals, and outcome evidence.",
      "prompt": "Run this when a customer requests an AI workflow, reports a failure, or reaches an operations review. Choose one priority, such as enriching leads, drafting emails, summarizing meetings, or updating a CRM. Define the owner, inputs, approvals, success metric, and ROI hypothesis. Dry-run it on realistic customer data, fix the smallest verified problem, then release through approved stages and monitor production. Finish with the outcome, evidence, customer update, lessons saved, and next review.",
      "useWhen": "Use this when an AI workflow must live inside a real customer process and needs validation, approval, gradual rollout, monitoring, and a clear business outcome.",
      "verification": "One customer priority reaches a proven terminal state. The workflow reaches its agreed rollout stage, a production issue is fixed, or a blocker is escalated with an owner and next step.",
      "steps": [
        "Review the customer priority, recent feedback, workflow history, failures, approvals, usage, cost, and ROI signals.",
        "Choose one workflow or improvement and define its owner, systems, data, risk, approval gates, success criteria, and ROI hypothesis.",
        "Dry-run it on realistic customer data, repair the smallest underlying issue, and release through controlled stages.",
        "Monitor production, send the customer update, and store reusable preferences, failures, examples, and ROI observations."
      ],
      "why": "The workflow itself is only one part of a real deployment. This loop keeps validation, approval, rollout, monitoring, learning, and accountability tied to one customer priority.",
      "notes": "Do not expand rollout when dry-run evidence, approval state, or monitoring is missing. Keep sensitive, irreversible, financial, and customer-facing actions behind explicit human approval.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/customer-ai-deployment-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "ticket-to-pr-ready-loop",
      "title": "Take a ticket to reviewer-ready",
      "url": "https://looprepo.dev/loops/ticket-to-pr-ready-loop",
      "loopType": "loop",
      "category": "debugging",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "ticket-to-pull-request",
        "bug-reproduction",
        "root-cause-analysis",
        "review-ready-patch"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Turn a ticket or bug report into a proven root cause, a minimal patch, and a clean handoff a reviewer can trust.",
      "prompt": "Take a ticket, bug report, failing behavior, or customer complaint and turn it into a review-ready patch. Reproduce the failure in the smallest representative environment, prove the root cause, make the smallest credible fix, and rerun the original reproduction plus relevant regression tests. If the issue cannot be reproduced after two serious attempts, say so. Do not fold unrelated refactors into the patch. Finish with the cause, changed files, before-and-after proof, risks, and pull-request summary.",
      "useWhen": "Use this when a real but loosely written ticket, bug report, or customer complaint needs to become a bounded engineering change with enough proof for a fast review.",
      "verification": "The failure is fixed, verified, and ready for review. The issue reproduces before the fix, no longer reproduces afterward, and relevant regression checks pass.",
      "steps": [
        "State the expected and actual behavior, then reproduce the failure in the smallest representative environment.",
        "Trace the behavior to a root cause and confirm the causal link with evidence.",
        "Implement the smallest credible fix, avoiding unrelated cleanup or hidden refactors.",
        "Repeat the original reproduction, run relevant regression checks, and package the result for review."
      ],
      "why": "The loop closes the gap between something being wrong and a reviewer being able to trust the patch. Reproduction, evidence, bounded scope, and a structured handoff remove the detective work from review.",
      "notes": "Match the proof to the failure: screenshots or recordings for UI issues, tests or logs for backend behavior, benchmark deltas for performance, and sanitized traces for integrations.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/ticket-to-pr-ready-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "post-release-baseline-loop",
      "title": "Capture a post-release baseline",
      "url": "https://looprepo.dev/loops/post-release-baseline-loop",
      "loopType": "loop",
      "category": "devops",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-release-operations",
        "post-release-benchmark",
        "performance-baseline",
        "release-verification",
        "benchmark-history"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Run the standard benchmarks against a finished release and record a reproducible baseline for future comparison.",
      "prompt": "After current releases finish, run the standard benchmarks and record the results as the new baseline.",
      "useWhen": "Use this immediately after a release when future regressions or improvements need to be measured against the exact version now in production.",
      "verification": "The new baseline belongs to the completed release. Revision, environment, benchmark version, conditions, and results are recorded together.",
      "steps": [
        "Confirm every in-scope release is complete and record the production revision or artifact identity.",
        "Run the standard benchmark suite under its documented environment, data, warm-up, and repetition rules.",
        "Investigate invalid or unstable runs, then rerun only under the same documented conditions.",
        "Store the final results with the release identity and benchmark metadata, and mark them as the new comparison baseline."
      ],
      "why": "Tying the baseline to a verified release creates a trustworthy reference point for later performance and quality work. Recording the conditions prevents unrelated environment changes from masquerading as product changes.",
      "notes": "Do not overwrite the previous baseline until the release identity and benchmark run are verified. Keep historical baselines available for trend analysis.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/post-release-baseline-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "production-data-cleanup-loop",
      "title": "Clean production data to spec",
      "url": "https://looprepo.dev/loops/production-data-cleanup-loop",
      "loopType": "loop",
      "category": "database",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-data-operations",
        "production-data-cleanup",
        "classification-logic",
        "data-quality-audit",
        "regression-examples"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Remove disallowed records, sharpen the classification logic, and verify the remaining dataset against an explicit definition.",
      "prompt": "Review production records, remove anything that does not meet the allowed definition, improve the classification logic, and verify the remaining data.",
      "useWhen": "Use this when a production dataset contains records that no longer match a product, policy, taxonomy, or quality definition and the classifier allowed them through.",
      "verification": "Every remaining record meets the allowed definition. Representative classification tests and a post-cleanup audit prove the retained data is valid.",
      "steps": [
        "Write the allowed definition as explicit inclusion, exclusion, and edge-case rules before changing data.",
        "Audit production records, preserve a recoverable record of proposed removals, and separate clear violations from uncertain cases.",
        "Remove confirmed invalid records through the approved production path and improve the classifier with regression examples.",
        "Rerun classification tests and audit the remaining production data until every sampled and queried record meets the definition."
      ],
      "why": "Fixing both the existing records and the classifier closes the immediate data problem and reduces recurrence. Explicit rules and regression examples make future cleanup decisions reviewable.",
      "notes": "Follow access, retention, privacy, and audit requirements. Use backups or reversible operations where appropriate, and do not delete uncertain records without review.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/production-data-cleanup-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "stale-safe-batch-release-loop",
      "title": "Batch a release without the stale work",
      "url": "https://looprepo.dev/loops/stale-safe-batch-release-loop",
      "loopType": "loop",
      "category": "devops",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-release-operations",
        "batch-release",
        "stale-code-prevention",
        "pull-request-coordination",
        "deployment-safety"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Exclude unfinished or stale branches, combine the valid changes, and ship a complete artifact from the latest integrated main.",
      "prompt": "Review pending changes and pull requests, exclude stale or unfinished work, combine the valid changes, and release them together.",
      "useWhen": "Use this when several branches or pull requests may be ready at once and the release must avoid stale worktrees, partial overlays, and incomplete changes.",
      "verification": "Only current, complete changes ship in the combined release. The released revision is the latest integrated main that contains every selected change.",
      "steps": [
        "Fetch current repository and pull-request state, then inspect every candidate change for freshness, completeness, ownership, checks, and dependencies.",
        "Exclude stale, superseded, conflicting, or unfinished work and record why each candidate was omitted.",
        "Integrate the valid changes, rerun the combined checks, and select the newest main revision that contains the full batch.",
        "Release complete artifacts from a clean checkout, serialize the deployment, and verify production before closing the batch."
      ],
      "why": "Evaluating all candidates before integration prevents stale code from entering a release through convenience or worktree confusion. Releasing from integrated main proves the deployed artifact matches the reviewed batch.",
      "notes": "The candidate diff selects what belongs in the batch, but deployment must use complete artifacts from the latest integrated main. Never deploy from a task worktree or partial file overlay.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/stale-safe-batch-release-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "repository-cleanup-loop",
      "title": "Clean out stale repo state",
      "url": "https://looprepo.dev/loops/repository-cleanup-loop",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "repository-cleanup",
        "git-worktree-audit",
        "branch-hygiene",
        "pull-request-triage"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Audit branches, PRs, commits, and worktrees; rescue anything valuable; then delete what's provably stale.",
      "prompt": "Inspect local and remote branches, pull requests, commits, and worktrees. Recover valuable work and clean everything stale until the repository is current and organized.",
      "useWhen": "Use this when abandoned branches, old worktrees, unclear pull requests, or unmerged commits make it difficult to know which repository state still matters.",
      "verification": "Valuable work is recovered and remaining repository state is intentional. Branches, pull requests, commits, and worktrees are current, owned, or safely removed with evidence.",
      "steps": [
        "Inventory local and remote branches, open and recently closed pull requests, unmerged commits, and registered worktrees.",
        "Classify each item as current, valuable but unfinished, superseded, merged, abandoned, or uncertain, recording evidence and ownership.",
        "Recover valuable changes into an appropriate current branch before removing any stale reference.",
        "Clean only proven stale state, fetch and prune safely, then rerun the inventory until every remaining item is intentional."
      ],
      "why": "Inventory and classification separate recoverable work from clutter before cleanup begins. Repeating the inventory proves the repository is organized instead of merely smaller.",
      "notes": "Do not delete uncertain work, discard uncommitted changes, or close someone else's pull request without confirmation. Preserve evidence for every destructive cleanup action.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/repository-cleanup-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "test-suite-speed-loop",
      "title": "Make the test suite fast",
      "url": "https://looprepo.dev/loops/test-suite-speed-loop",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "test-suite-performance",
        "faster-ci",
        "test-optimization",
        "coverage-preservation"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Cut test runtime under repeatable conditions without weakening coverage, assertions, isolation, or behavior.",
      "prompt": "Optimize the test suite to run as quickly as possible without reducing coverage or changing behavior.",
      "useWhen": "Use this when slow tests are delaying local feedback or continuous integration and the project has stable commands for measuring runtime and coverage.",
      "verification": "The suite is faster with no coverage or behavior regression. Repeatable timing, the full passing suite, and the original coverage report prove the result.",
      "steps": [
        "Record the full-suite runtime, coverage, environment, worker settings, and repeatable timing method.",
        "Profile the suite to find expensive setup, redundant work, poor isolation, unnecessary integration paths, or safe parallelization opportunities.",
        "Make one optimization at a time, then rerun the full suite and compare timing, coverage, and behavior.",
        "Stop at the agreed runtime target or diminishing-returns rule with all original checks still passing."
      ],
      "why": "A fixed baseline prevents speed work from quietly trading away coverage or correctness. Profiling directs effort toward measured bottlenecks instead of speculative rewrites.",
      "notes": "Define a runtime target or diminishing-returns rule before starting. Faster tests are not an improvement if they become flaky, order-dependent, or less representative.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/test-suite-speed-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "full-product-evaluation-loop",
      "title": "Evaluate the whole product to a bar",
      "url": "https://looprepo.dev/loops/full-product-evaluation-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "production-grade-qa",
        "production-like-local-testing",
        "exhaustive-product-testing",
        "real-user-testing",
        "ui-control-coverage",
        "edge-case-testing"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Run realistic scenarios across every major capability, fix weak outcomes, and rerun until each clears the defined bar.",
      "prompt": "Build sanitized, production-scale local data under production-like settings. Inventory every user-facing feature, role, route, button, input, modal, state, and workflow; define documented acceptance criteria and finite risk-based edge cases for each. Test as a real user, logging every bug with reproduction evidence. Review findings for shared causes and dependencies; implement coherent fixes with regression tests, then rerun the full inventory. Stop at a clean pass or blocked handoff. Ask before production, sensitive data, or destructive actions.",
      "useWhen": "Use this for an exhaustive, end-to-end application QA pass when a production-like local environment and complete interactive-surface coverage matter more than a narrow regression or sample of major features.",
      "verification": "Every inventoried product surface meets its documented acceptance criteria. The final full regression run covers every inventoried surface and its finite risk-based edge cases in the production-like local environment, with each reproducible bug fixed and backed by evidence.",
      "steps": [
        "Build a sanitized or synthetic production-scale local dataset, mirror safe production settings, and record unavoidable differences.",
        "Inventory every user-facing feature, role, route, control, state, and workflow; define documented acceptance criteria and a finite risk-based edge-case set for each item.",
        "Exercise every inventory item as a real user under its normal and defined edge-case conditions, logging each bug immediately with reproducible evidence.",
        "Review the complete bug set for shared causes, dependencies, and conflicting fixes, then implement the smallest coherent solution with regression coverage.",
        "Rerun affected paths and the complete inventory; stop only at a clean full pass or an explicit blocked handoff."
      ],
      "why": "A finite surface inventory prevents major controls and states from disappearing behind a few happy-path scenarios. Reviewing all findings before fixing them exposes shared causes and interactions, while the final full run catches changes that repair one path but weaken another.",
      "notes": "Do not copy secrets or sensitive production data into the local environment, touch production without approval, or count an untested or blocked surface as passing. Preserve the inventory, bug log, environment differences, and final evidence for review.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/full-product-evaluation-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "quality-streak-loop",
      "title": "Turn every bug into a regression test",
      "url": "https://looprepo.dev/loops/quality-streak-loop",
      "loopType": "loop",
      "category": "evaluation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-product-evaluation",
        "quality-streak",
        "regression-testing",
        "benchmark-coverage",
        "realistic-scenarios"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Test like a real user, convert each failure into documented regression coverage, and restart the streak after every fix.",
      "prompt": "Test realistic scenarios. When one fails, document it, add regression and benchmark coverage, fix it, and restart the streak. Stop after [N] successful cases in a row.",
      "useWhen": "Use this when product quality needs a strict consecutive-success bar and failures should permanently improve the test and benchmark suite.",
      "verification": "The latest [N] realistic cases pass in a row. Every earlier failure is documented, fixed, and protected by regression and benchmark coverage.",
      "steps": [
        "Define realistic scenarios, the quality bar, the value of [N], and the evidence required for a pass.",
        "Run cases one at a time under consistent conditions and preserve the result for review.",
        "On any failure, document it, add regression and benchmark coverage, fix the cause, verify the fix, and reset the streak to zero.",
        "Stop only after [N] consecutive cases meet the original quality bar."
      ],
      "why": "Restarting the streak prevents isolated successes from hiding intermittent weaknesses. Converting each failure into durable coverage makes the evaluation stronger after every miss.",
      "notes": "Choose [N] before the run and keep the scenario distribution representative. Do not lower the quality bar or avoid difficult cases to preserve the streak.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/quality-streak-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "nightly-changelog-sweep",
      "title": "Keep the changelog current nightly",
      "url": "https://looprepo.dev/loops/nightly-changelog-sweep",
      "loopType": "schedule",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "nightly-changelog",
        "release-notes-workflow",
        "changelog-automation",
        "daily-repository-review"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Review yesterday's changes each night and keep user-facing release history complete and accurate.",
      "prompt": "Each night, review changes from the previous day and update the changelog with anything users should know.",
      "useWhen": "Use this when a project changes frequently enough that user-facing release notes can drift from merged pull requests, commits, deployments, and product changes.",
      "verification": "Every user-relevant change from the previous day is accounted for. The changelog is updated and validated, or the no-change result is recorded.",
      "steps": [
        "Collect the previous day's merged pull requests, commits, deployments, and other in-scope changes.",
        "Identify which changes affect users and compare them with the current changelog.",
        "Add concise dated entries with useful references while preserving existing content and avoiding duplicates.",
        "Run the relevant checks and record either the validated update or the fact that no user-facing entry was needed."
      ],
      "why": "A daily reconciliation makes omissions visible while the context is still fresh. Limiting entries to what users should know keeps the changelog useful instead of turning it into a raw commit feed.",
      "notes": "Use the underlying change and product behavior as the source of truth. Commit titles alone can overstate, understate, or misclassify what users experienced.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/nightly-changelog-sweep/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "exhaustive-logging-coverage-loop",
      "title": "Add the logs you're missing",
      "url": "https://looprepo.dev/loops/exhaustive-logging-coverage-loop",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "structured-logging",
        "observability-coverage",
        "logging-tests",
        "production-diagnostics"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Audit the important code paths, add useful structured logs, and prove success and failure events fire with tests.",
      "prompt": "Review the system's logging and add missing coverage until every important path produces useful, tested logs.",
      "useWhen": "Use this when important user flows, service boundaries, background jobs, or failure paths are difficult to trace because the system's logging is incomplete or inconsistent.",
      "verification": "Every important path emits useful, tested logs. Representative success and failure tests prove coverage without exposing sensitive data.",
      "steps": [
        "Inventory the important paths and define the event, outcome, severity, correlation context, and fields each one should emit.",
        "Add structured logs to uncovered paths without duplicating events or adding low-value noise.",
        "Add tests for successful and failed outcomes, then inspect representative emitted logs for useful context.",
        "Verify redaction and repeat until every important path has tested coverage or a documented reason not to log."
      ],
      "why": "Treating logging as testable coverage turns observability from scattered statements into a reviewable system requirement. Inspecting emitted events catches gaps that source review alone misses.",
      "notes": "Never log credentials, tokens, secrets, or sensitive personal data. Prefer stable event names and structured fields over interpolated prose.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/exhaustive-logging-coverage-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "seo-geo-visibility-loop",
      "title": "Close your search-visibility gaps",
      "url": "https://looprepo.dev/loops/seo-geo-visibility-loop",
      "loopType": "goal",
      "category": "content",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "seo-audit",
        "generative-engine-optimization",
        "geo-workflow",
        "ai-search-visibility",
        "answer-engine-optimization"
      ],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Fix the highest-impact crawl, indexation, intent, citation, and answer-readiness gaps first, in priority order.",
      "prompt": "Run an SEO/GEO audit across crawlability, indexation, page intent, titles, internal links, structured data, source citations, and answer-first content. Rank the gaps by expected impact, fix the highest-leverage issue, then rerun the same crawl and target-query benchmark across search engines and AI answer engines. Repeat until no critical technical issues remain, every priority query maps to a clear answer-ready page, and the benchmark shows no high-impact gap left to fix.",
      "useWhen": "Use this when a site has a defined set of priority pages and target questions, and you can rerun the same technical crawl and search visibility checks after each change.",
      "verification": "Priority pages are indexable, answer-ready, and technically sound. The repeatable crawl and query benchmark finds no remaining high-impact gaps.",
      "steps": [
        "Record the target queries, answer engines, search engines, locale, date, and benchmark method.",
        "Audit crawlability, indexation, page intent, titles, internal links, structured data, citations, and visible answer quality.",
        "Rank findings by expected impact and fix one high-leverage issue at a time.",
        "Rerun the original crawl and query benchmark until no critical technical issue or high-impact content gap remains."
      ],
      "why": "A fixed benchmark makes visibility work measurable and prevents a long list of low-value SEO tasks from replacing the highest-impact fix. Mapping each priority query to a strong page also gives search and answer systems a clear destination.",
      "notes": "AI citations and search results vary by time, location, account state, and model. Record the test conditions and treat sampled visibility as evidence, not a guaranteed ranking.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/seo-geo-visibility-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "100-percent-test-coverage-loop",
      "title": "Drive coverage to 100%",
      "url": "https://looprepo.dev/loops/100-percent-test-coverage-loop",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "100-percent-test-coverage",
        "test-coverage-workflow",
        "automated-testing",
        "coding-agent-prompt"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Find uncovered behavior, add tests that actually matter, and stop when the full suite passes at 100%.",
      "prompt": "Add tests until we have 100% test coverage.",
      "useWhen": "Use this when 100% coverage is an explicit project requirement and the repository has a trustworthy coverage command, clear exclusions, and a test suite that can be run repeatedly.",
      "verification": "The full test suite passes at 100% coverage. Use the project's coverage report as the source of truth.",
      "steps": [
        "Run the complete test suite with coverage and save the baseline report.",
        "Prioritize uncovered branches and behavior by risk instead of file order.",
        "Add tests that assert meaningful outcomes, failure paths, and boundary conditions.",
        "Repeat until the full suite passes and the configured coverage report reaches 100%."
      ],
      "why": "A concrete coverage target gives the agent a measurable stopping condition and makes skipped code visible. Risk-first ordering keeps the work focused on behavior that matters.",
      "notes": "Coverage measures which code ran, not whether the assertions are good. Review test quality, avoid tests that only execute lines, and keep justified generated-code or platform exclusions explicit.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/100-percent-test-coverage-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "production-error-sweep",
      "title": "Sweep production errors to root cause",
      "url": "https://looprepo.dev/loops/production-error-sweep",
      "loopType": "loop",
      "category": "debugging",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "production-log-review",
        "error-triage",
        "root-cause-analysis",
        "reliability-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Trace actionable production errors to their root cause, verify the fix, open a PR, and stop cleanly when nothing needs action.",
      "prompt": "Review our production logs for errors. If you find an actionable issue, trace it to its root cause, fix it, verify the fix, and open a pull request. If no actionable errors are present, stop without making changes.",
      "useWhen": "Use this as a scheduled reliability pass when an agent can read production telemetry, trace failures into the repository, run the relevant tests, and prepare a reviewable fix.",
      "verification": "Actionable production errors are fixed and verified. Finish with a pull request, or stop when no actionable errors are present.",
      "steps": [
        "Review the agreed production log window and group repeated symptoms into likely incidents.",
        "Separate actionable product errors from expected noise, transient upstream failures, and already-known issues.",
        "Trace each actionable error to a root cause, implement the smallest appropriate fix, and verify it with focused checks.",
        "Open a pull request for each verified fix. If the logs are clean, stop without making changes."
      ],
      "why": "The loop converts passive log review into a closed reliability workflow. It requires a root cause, verified change, and review artifact instead of stopping at a list of errors.",
      "notes": "Treat logs as sensitive production data. Do not copy credentials, tokens, personal information, or private payloads into prompts, pull requests, or chat messages.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/production-error-sweep/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "sub-50ms-page-load-loop",
      "title": "Get every page under 50 ms",
      "url": "https://looprepo.dev/loops/sub-50ms-page-load-loop",
      "loopType": "goal",
      "category": "performance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "page-load-optimization",
        "performance-benchmark",
        "web-performance-workflow",
        "50-ms-page-load"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Benchmark each page with one repeatable measure and keep optimizing until every target loads under the threshold.",
      "prompt": "Continue optimizing the code for speed. After each significant change, measure page-load performance across every page under the same repeatable test conditions. Continue until every page loads in under 50 ms.",
      "useWhen": "Use this when a product has a defined set of routes, a stable performance harness, and a 50 ms target that maps to a specific metric and environment.",
      "verification": "Every page loads in under 50 ms. Use the same benchmark and confirm there are no regressions.",
      "steps": [
        "Define the exact metric, routes, test environment, warm-up behavior, and number of benchmark runs.",
        "Capture a baseline for every target page before making changes.",
        "Make one significant optimization, rerun the same benchmark, and inspect regressions across all routes.",
        "Continue until every page meets the threshold under the original test conditions."
      ],
      "why": "The fixed harness prevents performance work from turning into anecdotal tuning. Measuring every route after each change catches local wins that quietly slow down another page.",
      "notes": "Page load can mean server response, render completion, or a browser timing metric. Name the metric and hardware explicitly so the 50 ms target is reproducible and meaningful.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/sub-50ms-page-load-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "architecture-satisfaction-loop",
      "title": "Refactor in tested checkpoints",
      "url": "https://looprepo.dev/loops/architecture-satisfaction-loop",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "architecture-refactor",
        "autoreview",
        "incremental-refactoring",
        "coding-agent-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Reshape the architecture in small, independently reviewed steps — live-test, commit a checkpoint, and log progress each pass.",
      "prompt": "Refactor until you are happy with the architecture. After each significant step, live-test the system, run autoreview, and commit. Track progress in /tmp/refactor-{projectname}.md.",
      "useWhen": "Use this for a deliberate architectural refactor where the destination can be stated in concrete terms and the current system can be tested after each meaningful change.",
      "verification": "The architecture is satisfactory and checks pass. Live-test, autoreview, and commit each significant step.",
      "steps": [
        "Write down the architectural target, constraints, and current risks before editing code.",
        "Make one significant, reviewable change at a time.",
        "Live-test the affected behavior and run an independent review after each significant step.",
        "Commit each verified checkpoint and update the temporary progress file with decisions, blockers, and the next action."
      ],
      "why": "Small verified checkpoints reduce refactor risk and preserve rollback points. The progress file keeps the goal and decisions available across long sessions or handoffs.",
      "notes": "Define what satisfactory means before starting, such as module boundaries, dependency direction, passing tests, and acceptable performance. A subjective stop condition can otherwise run indefinitely.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/architecture-satisfaction-loop/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "overnight-docs-sweep",
      "title": "Fix doc drift, ship a PR",
      "url": "https://looprepo.dev/loops/overnight-docs-sweep",
      "loopType": "schedule",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ai-coding-agent",
        "documentation-audit",
        "documentation-drift",
        "documentation-maintenance",
        "pull-request-workflow"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Forward Future",
        "authority": 80,
        "githubStars": null
      },
      "description": "Compare every doc against the current code, fix what's stale, verify commands and links, and open a reviewable PR.",
      "prompt": "Whenever a documentation pass is needed, review the codebase in full and make sure all documentation reflects the current implementation. Update stale documentation, verify the changes, then open a pull request.",
      "useWhen": "Use this whenever implementation changes may have left READMEs, setup guides, API references, examples, or runbooks behind.",
      "verification": "Documentation matches the current implementation. Finish with a reviewable pull request.",
      "steps": [
        "Review implementation changes since the last documentation pass.",
        "Compare the repository's documentation with the code, configuration, commands, and behavior that now ship.",
        "Update only stale material, then verify commands, links, and examples against the current repository.",
        "Run the relevant checks and open a pull request that explains the documentation drift and the fixes."
      ],
      "why": "The loop ties documentation to the implementation instead of relying on memory. Requiring a pull request creates a visible diff, a review point, and a durable record of what changed.",
      "notes": "Keep the scope tied to real implementation changes. Do not rewrite accurate documentation just to create activity.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Forward Future",
        "url": "https://signals.forwardfuture.com/loop-library/loops/overnight-docs-sweep/"
      },
      "published": "2026-07-03"
    },
    {
      "slug": "weekdays-at-9am-review-open-prs-assigned-to",
      "title": "Weekdays at 9am: review open PRs assigned to you",
      "url": "https://looprepo.dev/loops/weekdays-at-9am-review-open-prs-assigned-to",
      "loopType": "schedule",
      "category": "review",
      "difficulty": "beginner",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "ShilpaMitra",
        "authority": 40,
        "githubStars": null
      },
      "description": "A scheduled Routine that runs each weekday at 9am to review the open pull requests assigned to you and leave a first-pass review on each, running in the cloud even with your computer off.",
      "prompt": "/schedule weekdays at 9am: review open PRs assigned to me, leave a first-pass",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: to start each workday with a first-pass review already drafted on your assigned PRs. Safety: it leaves review comments only — it does not approve or merge, so human sign-off is preserved. Scope it to PRs assigned to you so it does not comment across the whole repo.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "ShilpaMitra",
        "url": "https://www.reddit.com/r/WebAfterAI/comments/1u0c6so/5_claude_code_automation_setups_that_keep_working/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "check-whether-the-deploy-finished-and-summarize-what",
      "title": "Check whether the deploy finished and summarize what changed",
      "url": "https://looprepo.dev/loops/check-whether-the-deploy-finished-and-summarize-what",
      "loopType": "loop",
      "category": "devops",
      "difficulty": "beginner",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "ShilpaMitra",
        "authority": 40,
        "githubStars": null
      },
      "description": "A 5-minute watch loop that polls whether a deploy has finished and, once it lands, summarizes what changed. It is a read-only status watcher rather than an agent driving toward a finish condition.",
      "prompt": "/loop 5m check whether the deploy finished and summarize what changed",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: while waiting on a deploy and you want a hands-off heads-up the moment it completes. Safety: observational only — it reports on the deploy, it never triggers, promotes, or rolls one back. Session-scoped: it runs only while the terminal stays open; use /schedule for a version that survives a closed terminal.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "ShilpaMitra",
        "url": "https://www.reddit.com/r/WebAfterAI/comments/1u0c6so/5_claude_code_automation_setups_that_keep_working/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "content-operations-monitor-via-custom-loop-md",
      "title": "Content operations monitor via custom loop.md",
      "url": "https://looprepo.dev/loops/content-operations-monitor-via-custom-loop-md",
      "loopType": "loop",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "Koka Sexton",
        "authority": 40,
        "githubStars": null
      },
      "description": "A marketing-facing loop.md playbook that turns a bare /loop into a recurring content-ops sweep: checks GA4 for week-over-week organic traffic drops, scans GSC for position 4-15 query opportunities, and audits WordPress posts for broken internal links and missing meta descriptions — reporting one line when everything is green.",
      "prompt": "/loop 15m\n\n(Save the following as .claude/loop.md so the bare /loop picks it up as its playbook.)\n\n# .claude/loop.md — Content Operations Monitor\nCheck the following every iteration:\n1. Pull the latest GA4 data for kokasexton.com. If any post dropped more than 30% in organic traffic week-over-week, flag it with the URL and the percentage drop.\n2. Scan GSC for new queries where we rank positions 4-15 and impressions grew >20% week-over-week. List the top 3 opportunities.\n3. Check the WordPress admin for any posts with broken internal links or missing meta descriptions. Fix silently if fewer than 5 issues. Report if more.\n4. If everything is green, reply with one line: \"Content ops clean — nothing needs attention.\"",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Requires GA4/GSC/WordPress access via MCP connectors before it can do anything useful — without them the loop will hallucinate or no-op. Step 3 lets the agent fix issues silently below a threshold; run with a scoped WordPress account and review the first few iterations before trusting silent fixes. Replace kokasexton.com with your own property. Loops expire after 7 days by default in Claude Code, which caps runaway cost.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Koka Sexton",
        "url": "https://kokasexton.com/claude-code-loops-automate-your-work-while-you-do-something-else/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "custom-loop-md-project-level-default-for-bare-loop",
      "title": "Custom loop.md — Project-Level Default for Bare /loop",
      "url": "https://looprepo.dev/loops/custom-loop-md-project-level-default-for-bare-loop",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "claudefa.st",
        "authority": 40,
        "githubStars": null
      },
      "description": "A team-config pattern: a loop.md file in the project root overrides the built-in maintenance prompt, so any teammate running bare /loop gets your project's canonical loop — run lint, typecheck, and tests, fix anything red, stop when clean.",
      "prompt": "Put a `loop.md` in the project root to replace the built-in maintenance prompt when a user runs bare `/loop` — e.g., \"run lint + typecheck + tests; fix anything red; update CHANGELOG; stop when clean.\" Every teammate's bare `/loop` now runs your loop.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: your team runs bare /loop often enough that the built-in default maintenance prompt is a missed opportunity — you want every teammate's reflexive /loop to run your project's canonical checklist instead. How it works: place a loop.md file in the project root; it replaces the built-in maintenance prompt whenever someone runs bare /loop. A typical loop.md: run lint, typecheck, and tests; fix anything red; update the CHANGELOG; stop when clean. Because the file is versioned with the repo, the team's default loop evolves through normal code review. Safety: this is configuration, not a runnable loop itself — the safety of bare /loop becomes whatever your loop.md says, so write an explicit stop condition (stop when clean) and keep the scope conservative, since people will invoke it casually. Note the documented limit: loop.md maxes out at 25KB per Anthropic's docs. Review changes to it like code, because it is code.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "claudefa.st",
        "url": "https://claudefa.st/blog/guide/mechanics/autonomous-agent-loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "codex-app-automations-scheduled-agent-runs",
      "title": "Codex App Automations (Scheduled Agent Runs)",
      "url": "https://looprepo.dev/loops/codex-app-automations-scheduled-agent-runs",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "official",
        "label": "OpenAI",
        "authority": 100,
        "githubStars": null
      },
      "description": "Codex's native answer to scheduled agent loops: define a prompt plus a schedule in the Codex app and it runs in the cloud on cadence — nightly dependency audits, morning issue triage — with no terminal open. The Codex-side equivalent of Claude Code Routines.",
      "prompt": "Define an Automation in the Codex app: a prompt + schedule that runs in the cloud on cadence (e.g., nightly dependency audit, morning triage of new issues), no terminal open.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: recurring agent work on the Codex side of the fence — nightly dependency audits, morning triage of new issues — where you want cloud execution on a schedule with no terminal open. It is the Codex-side equivalent of Claude Code Routines. How it works: define an Automation in the Codex app: a prompt plus a schedule. The automation then runs in the cloud on that cadence — your machine can be off entirely. Note this is a Codex-app pattern, not a Claude slash command; it is filed in this directory as a harness pattern. Safety: cloud-scheduled agents run unattended by definition, so the discipline lives in the prompt: give automations report-shaped work (audit, triage, summarize) before mutation-shaped work, and make any write action land as a reviewable artifact — a PR or an issue — rather than a direct change. Review the first few scheduled outputs before extending its scope.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "OpenAI (Codex app docs)",
        "url": "https://developers.openai.com/codex/app/automations"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-overnight-builds-progressive-curriculum-entry",
      "title": "Ralph Overnight Builds — Progressive Curriculum Entry",
      "url": "https://looprepo.dev/loops/ralph-overnight-builds-progressive-curriculum-entry",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "Claude Code Masterclass newsletter",
        "authority": 40,
        "githubStars": null
      },
      "description": "A graduated path to unattended Ralph runs: start with a single bounded task, add a PROMPT.md spec file, add verification, and only then remove the human from the loop for overnight builds.",
      "prompt": "Staged path from basic prompt → PROMPT.md spec → overnight Ralph run: start with a single bounded task, add a spec file, add verification, only then remove the human from the loop.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you are tempted by overnight Ralph runs but have not run one before — this is the curriculum that gets you there without learning each failure mode the expensive way. How it works: a staged path where each stage adds one piece of rigor. Start with a single bounded task run under supervision. Then move the task definition into a PROMPT.md spec file. Then add verification, so done is machine-checked rather than asserted. Only after all three are solid do you remove the human from the loop and let it run overnight. Each stage exercises the discipline the next one depends on. Safety: the sequencing is the safety mechanism — unattended operation is earned last, after bounded scope, a written spec, and objective verification are already proven on supervised runs. Most overnight-loop disasters trace to a skipped stage. When you do go unattended, add the standard rails: iteration caps, budget limits, sandbox, branch.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Claude Code Masterclass newsletter",
        "url": "https://newsletter.claudecodemasterclass.com/p/claude-code-ralph-loop-from-basic"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "runaway-bill-guardrail-loop-watchdog-beside-the-worker",
      "title": "Runaway-Bill Guardrail Loop (Watchdog Beside the Worker)",
      "url": "https://looprepo.dev/loops/runaway-bill-guardrail-loop-watchdog-beside-the-worker",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 60
      },
      "provenance": {
        "tier": "community",
        "label": "devtoolpicks",
        "authority": 40,
        "githubStars": null
      },
      "description": "A cost-safety pattern that pairs every overnight loop with a second, dumber loop whose only job is stopping the first: spend alerts, a hard iteration cap, and a cron check that kills the worker when token burn spikes or the same command keeps repeating.",
      "prompt": "Pair every overnight loop with a watchdog: spend/usage alert thresholds, a hard `MAX_ITER`, and a cron check that kills the loop process if tokens-per-minute spikes or the same command repeats N times. The watchdog is a second, dumber loop whose only job is stopping the first one.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: alongside every overnight or unattended loop you run — this is not a work loop but the watchdog you pair with one, built for the wake-up-to-a-huge-bill failure mode. How it works: the worker loop gets a companion: spend and usage alert thresholds, a hard MAX_ITER cap, and a cron check that kills the worker process outright if tokens-per-minute spikes or the same command repeats N times in a row. The watchdog is deliberately a second, dumber loop whose only job is stopping the first one — it makes no judgment calls beyond its thresholds. Safety: the design principle is separation — the safety mechanism runs outside the worker's process and context, so a worker that has gone sideways cannot reason its way past its own limits. Repeated-command detection catches stuck loops that spend without progressing. Tune the thresholds to your loop's normal profile first, or the watchdog cries wolf.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "devtoolpicks",
        "url": "https://devtoolpicks.com/blog/ai-agents-runaway-claude-code-bills-overnight-2026"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "karpathy-style-claude-md-self-check-protocol-for-loops",
      "title": "Karpathy-Style CLAUDE.md Self-Check Protocol for Loops",
      "url": "https://looprepo.dev/loops/karpathy-style-claude-md-self-check-protocol-for-loops",
      "loopType": "ralph",
      "category": "quality",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Andrej Karpathy",
        "authority": 80,
        "githubStars": null
      },
      "description": "A self-check protocol embedded in CLAUDE.md that every loop iteration obeys before ending a turn: re-read the goal, diff the changes against it, run the verification command, and state what remains — a ritual that catches drift between iterations.",
      "prompt": "Preamble rules embedded in CLAUDE.md that every loop iteration obeys: before ending a turn, re-read the goal, diff your changes against it, run the verification command, and explicitly state what remains — a self-check ritual that catches drift between iterations. (Community template descended from Andrej Karpathy's circulated CLAUDE.md rules.)",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: loops that drift — iterations that wander off-goal, declare premature success, or lose track of remaining work — where you want a correcting ritual applied every single turn without re-prompting. How it works: preamble rules embedded in CLAUDE.md that every loop iteration obeys before ending a turn: re-read the goal, diff your changes against it, run the verification command, and explicitly state what remains. Because CLAUDE.md is loaded every session, the ritual survives fresh-context iterations for free — drift correction as standing configuration rather than per-run prompting. Safety: the run-the-verification-command step keeps self-assessment anchored to an objective check instead of the model's optimism. One attribution caution from the source: this is a community template descended from Karpathy's circulated CLAUDE.md rules, reported by a secondary source — verify the exact current rule text against the upstream repo before quoting or republishing specific rules.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Tech Times",
        "url": "https://www.techtimes.com/articles/319214/20260628/karpathy-claudemd-grows-ten-rules-new-self-check-protocol-ai-coding-loops.htm"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "issue-to-merge-github-native-loop-engineer-the-reload",
      "title": "Issue-to-Merge GitHub-Native Loop (Engineer the Reload)",
      "url": "https://looprepo.dev/loops/issue-to-merge-github-native-loop-engineer-the-reload",
      "loopType": "ralph",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "Saulius (saulius.io)",
        "authority": 40,
        "githubStars": null
      },
      "description": "A full-lifecycle loop where every piece of workflow state lives in GitHub — issues, labels, PR comments — and repo files, so each cold-start session rehydrates from GitHub rather than a conversation. Built on the official claude-code-action.",
      "prompt": "Run Claude Code across the full lifecycle — issue intake → branch → implement → PR → review fixes → merge — with ALL workflow state externalized to GitHub (issues, labels, PR comments) and repo files. Each session starts cold and rehydrates from GitHub state; \"the chat being gone doesn't cost you anything.\"",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want an agent operating across the full delivery lifecycle — issue intake, branch, implement, PR, review fixes, merge — reliably enough that losing a session costs nothing. How it works: Claude Code runs the whole flow with all workflow state externalized to GitHub — issues, labels, PR comments — and repo files, built on the official claude-code-action. Each session starts cold and rehydrates entirely from GitHub state, which is the engineer-the-reload idea: the chat being gone doesn't cost you anything, because nothing important ever lived only in the conversation. Safety: externalized state is itself a rail — every decision and status change is visible in GitHub's audit surfaces (issue timelines, PR history) rather than an opaque transcript. The lifecycle includes merge, so govern that step with branch protection, required checks, and human approval; let the agent drive the process while the merge gate stays policy-controlled.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Saulius (saulius.io)",
        "url": "https://saulius.io/blog/claude-code-github-native-agent-issue-to-merge-loop"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "stop-hook-ralph-deterministic-loop-without-bash",
      "title": "Stop-Hook Ralph (Deterministic Loop Without Bash)",
      "url": "https://looprepo.dev/loops/stop-hook-ralph-deterministic-loop-without-bash",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "paddo.dev",
        "authority": 40,
        "githubStars": null
      },
      "description": "A Ralph variant that lives inside a single Claude Code session: a stop hook re-injects the task prompt whenever the agent tries to end its turn, trading the bash while-loop's fresh context for a persistent session.",
      "prompt": "Use a Claude Code stop hook that re-injects the task prompt whenever the agent tries to end its turn, until a completion condition or hard iteration cap is met — Ralph semantics inside one session instead of a bash `while` wrapper.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want Ralph-style relentless iteration but inside a single Claude Code session — no bash wrapper, no process management — and you accept persistent context instead of fresh context as the trade. How it works: a Claude Code stop hook intercepts the agent whenever it tries to end its turn and re-injects the task prompt, forcing another iteration until a completion condition or a hard iteration cap is met. That yields Ralph semantics — keep going until done — deterministically within one session, trading the bash while-loop's fresh-context-per-iteration for session continuity and its context accumulation. Safety: the source's warning is the rule: always include a hard iteration cap in the hook logic, because a stop hook with no cap is an infinite loop by construction — the agent literally cannot end its turn. Make the completion condition machine-checkable, and remember that accumulated context drifts; for very long runs, fresh-context Ralph resists drift better.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "paddo.dev",
        "url": "https://paddo.dev/blog/ralph-wiggum-autonomous-loops/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "codex-cli-as-an-mcp-tool-inside-an-agents-sdk-loop",
      "title": "Codex CLI as an MCP Tool Inside an Agents-SDK Loop",
      "url": "https://looprepo.dev/loops/codex-cli-as-an-mcp-tool-inside-an-agents-sdk-loop",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "official",
        "label": "OpenAI",
        "authority": 100,
        "githubStars": null
      },
      "description": "An outer-planner/inner-coder loop from an official OpenAI recipe: an Agents SDK orchestrator plans and verifies while Codex CLI, wrapped as an MCP server, performs one bounded code change per turn.",
      "prompt": "Wrap Codex CLI as an MCP server and drive it from an OpenAI Agents SDK orchestrator loop — the outer agent plans/verifies, the inner Codex call does one bounded code change per turn.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: workflows needing separation between planning and coding — you want an orchestrator that decides what to do and verifies outcomes, with the code-touching capability isolated behind a tool boundary. From an official OpenAI recipe. How it works: Codex CLI is wrapped as an MCP server, and an OpenAI Agents SDK orchestrator drives it in a loop: the outer agent plans the work and verifies results, while each inner Codex call performs exactly one bounded code change per turn. The MCP boundary makes the coder a discrete, inspectable tool call rather than an open-ended session. Safety: the outer-planner, inner-coder split is the structural rail — the agent that changes code is not the agent that judges whether the change succeeded, and each code mutation is bounded to one tool invocation. Put iteration and budget caps in the orchestrator loop, since it, not Codex, controls how many turns run.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "OpenAI Cookbook",
        "url": "https://cookbook.openai.com/examples/codex/codex_mcp_agents_sdk/building_consistent_workflows_codex_cli_agents_sdk"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "codex-ci-autofix-loop-fix-failing-github-actions",
      "title": "Codex CI Autofix Loop (Fix Failing GitHub Actions)",
      "url": "https://looprepo.dev/loops/codex-ci-autofix-loop-fix-failing-github-actions",
      "loopType": "ralph",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "official",
        "label": "OpenAI",
        "authority": 100,
        "githubStars": null
      },
      "description": "An event-triggered loop where a red GitHub Actions build invokes `codex exec` non-interactively with the failing logs and repo, and Codex proposes a fix as a PR or patch artifact — one bounded iteration per CI failure.",
      "prompt": "CI job: on workflow failure, run `codex exec` non-interactively with the failing logs + repo, have it generate and propose a fix (PR or patch artifact) automatically. `codex exec` runs one task and exits, so each CI failure is one bounded iteration.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: repetitive CI failures — lint drift, snapshot updates, simple breakages — where a competent first-pass fix attempt on every red build would save real triage time. How it works: a CI job triggers on workflow failure and runs codex exec non-interactively with the failing logs and the repo as context; Codex generates a fix and proposes it as a PR or a patch artifact. Because codex exec runs one task and exits, each CI failure is one bounded iteration — the event is the trigger, so there is no long-running process to babysit. Safety: the rail is stated plainly in the source guidance: configure it to propose a PR, never auto-merge — every fix must land through human review, and an auto-merge variant of this loop is unsafe. The one-shot-per-failure structure also self-limits spend. Watch the early PRs for fix quality before trusting the pattern on subtle failures.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "OpenAI Cookbook",
        "url": "https://developers.openai.com/cookbook/examples/codex/autofix-github-actions"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "codex-iterative-repair-loop-json-schema-review-repair",
      "title": "Codex Iterative Repair Loop (JSON-Schema Review → Repair)",
      "url": "https://looprepo.dev/loops/codex-iterative-repair-loop-json-schema-review-repair",
      "loopType": "ralph",
      "category": "review",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "official",
        "label": "OpenAI",
        "authority": 100,
        "githubStars": null
      },
      "description": "OpenAI's first-party loop recipe: a script alternates a Codex review pass that emits machine-readable findings with a repair pass fed those findings verbatim, looping until validation passes, attempts run out, progress stalls, or a decision needs human review.",
      "prompt": "Script alternates two `codex exec` calls: (a) review pass with a JSON schema output (\"list remaining issues as machine-readable findings\"), (b) repair pass fed those findings verbatim. Loop while findings remain, capped by max attempts. Stops for one of four reasons: validation passes, max attempts reached, remaining delta stops changing, or next decision needs human review.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: repair work you want structured rather than freeform — a codebase with known issues where you need machine-readable findings driving fixes, with clear stop conditions. This is OpenAI's first-party loop recipe. How it works: a script alternates two codex exec calls. The review pass emits remaining issues as machine-readable findings conforming to a JSON schema; the repair pass is fed those findings verbatim and fixes them. The loop continues while findings remain and halts for exactly one of four reasons: validation passes, max attempts are reached, the remaining delta stops changing between passes, or the next decision needs human review. Safety: the four enumerated stop conditions are the rail — stalled progress and needs-a-human are first-class exits rather than failure modes discovered later, and the attempt cap bounds spend. The JSON-schema findings double as an audit trail of what the loop believed was wrong at each pass.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "OpenAI Cookbook",
        "url": "https://developers.openai.com/cookbook/examples/codex/build_iterative_repair_loops_with_codex"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "cursor-iterate-until-tests-pass-never-touch-the-tests",
      "title": "Cursor \"Iterate Until Tests Pass, Never Touch the Tests\"",
      "url": "https://looprepo.dev/loops/cursor-iterate-until-tests-pass-never-touch-the-tests",
      "loopType": "ralph",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "community",
        "label": "Cursor blog",
        "authority": 40,
        "githubStars": null
      },
      "description": "First-party Cursor guidance for the iterate-until-green loop, with the key anti-reward-hacking clause: the agent may never modify the tests it is trying to satisfy. Works in Cursor, Claude Code /goal, and Codex.",
      "prompt": "\"Write code that makes these tests pass. Do NOT modify the tests. Keep iterating — run the suite, fix failures, run again — until all tests pass.\" (paraphrase of Cursor's official agent best-practices guidance)",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: any test-driven agent session where the tests define done — you have a failing suite (TDD-style or a regression pile) and want the agent iterating until green without the classic cheat. How it works: the instruction is a plain contract: write code that makes these tests pass, do NOT modify the tests, and keep iterating — run the suite, fix failures, run again — until all tests pass. This is first-party Cursor guidance from their agent best-practices, and the pattern translates directly to Claude Code /goal and to Codex. Safety: the never-touch-the-tests clause is the entire anti-reward-hacking rail — without it, the cheapest path to green is editing an assertion, and agents find cheap paths. State it explicitly every time. The residual check is yours: confirm at the end that the test files are untouched (a quick git diff on the test paths) and that the implementing code is honest.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Cursor blog",
        "url": "https://cursor.com/blog/agent-best-practices"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "loop-cost-guardrails-pattern",
      "title": "Loop cost guardrails pattern",
      "url": "https://looprepo.dev/loops/loop-cost-guardrails-pattern",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "community",
        "label": "Developers Digest",
        "authority": 40,
        "githubStars": null
      },
      "description": "The four-part cost guardrail every agent loop should ship with: a hard iteration cap, a stop-after-N-turns clause in the goal text, a budget limit on SDK loops, and a /cost check inside the loop body.",
      "prompt": "Every loop gets: `MAX_ITER=20` hard cap, \"or stop after N turns\" in the /goal text, `max_budget_usd` on SDK loops, and a /cost check in the loop body.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: before running any loop unattended — this is the checklist pattern for the most common loop disaster, discovering the overnight run cost fifty times your estimate. How it works: four guardrails, applied together rather than as alternatives. A hard MAX_ITER=20 cap in the loop wrapper bounds iterations mechanically. An or-stop-after-N-turns clause written into the /goal text bounds the in-session layer. max_budget_usd on SDK-driven loops bounds dollar spend directly. And a /cost check inside the loop body gives running visibility, so drift is observable mid-run instead of at invoice time. Safety: the redundancy is the design — each rail catches what another misses: the iteration cap stops infinite loops, the budget cap stops expensive-per-iteration loops, and the in-prompt clause survives contexts where the wrapper does not apply. Adopt all four as the default template for every loop you ship, not just the risky ones.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Developers Digest",
        "url": "https://www.developersdigest.tech/blog/loop-engineering-definitive-guide"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "schedules-goals-subagents-design-framework",
      "title": "Schedules + goals + subagents design framework",
      "url": "https://looprepo.dev/loops/schedules-goals-subagents-design-framework",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "notable",
        "label": "Lenny's Newsletter",
        "authority": 80,
        "githubStars": null
      },
      "description": "A design framework for AI agent loops built on three questions — when should it run (schedule), what does done mean (goal), and who does the isolated pieces (subagents) — with worked examples in Claude Code and Codex.",
      "prompt": "Design framework: choose schedule (when), goal (what done means), subagents (who does isolated pieces) — with worked examples in Claude Code and Codex.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: before building any nontrivial loop — this is a design framework, not a runnable loop, and it exists because most loop failures are design failures: fuzzy done conditions, wrong triggers, monolithic tasks. How it works: three questions structure the design. When should it run — that is the schedule. What does done mean — that is the goal, which must be concrete and checkable. Who does the isolated pieces — those are subagents, each taking a bounded slice of the work with its own context. The framework ships with worked examples in both Claude Code and Codex showing the questions applied to real automations. Safety: the discipline itself is the safety value — a loop with an explicit machine-checkable done condition and decomposed responsibilities is far less likely to run away than a vibes-based one. Whatever design emerges, still add the runtime rails: iteration caps, budgets, and review gates on anything that mutates.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Lenny's Newsletter",
        "url": "https://www.lennysnewsletter.com/p/how-to-design-ai-agent-loops-schedules"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "goal-routines-overnight-combo",
      "title": "/goal + Routines overnight combo",
      "url": "https://looprepo.dev/loops/goal-routines-overnight-combo",
      "loopType": "schedule",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "notable",
        "label": "Sabrina Ramonov",
        "authority": 80,
        "githubStars": null
      },
      "description": "The two-layer answer to how do I run this overnight: /goal drives in-session work to done, while a scheduled Routine keeps recurring unattended work running on Anthropic's cloud with your laptop closed.",
      "prompt": "/schedule a Routine (runs on Anthropic cloud, laptop closed) for recurring unattended work, and use `/goal` for in-session iterate-to-done — the two-layer overnight pattern.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: the how-do-I-run-this-overnight question — you want in-session work driven to completion while you watch, and recurring unattended work running with the laptop closed. This is the two-layer answer. How it works: /goal handles the in-session layer, iterating a task to its done condition while you are at the keyboard. /schedule creates a Routine for the recurring layer, which runs on Anthropic's cloud on cadence — no local machine required, laptop closed. The split is deliberate: goals are for converging on a defined outcome now, Routines are for standing work that should happen without you. Safety: the two layers carry different risk profiles. Goals run under your observation with your local permissions; Routines run unattended in the cloud, so scope what a Routine can touch conservatively and give it report-heavy, mutation-light work until you trust its judgment. Put turn caps in your goal text as usual.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Sabrina Ramonov",
        "url": "https://www.sabrina.dev/p/loop-engineering-claude-code-goal-routines"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "spec-first-ralph-plan-md-driven",
      "title": "Spec-first Ralph (PLAN.md-driven)",
      "url": "https://looprepo.dev/loops/spec-first-ralph-plan-md-driven",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "HumanLayer",
        "authority": 80,
        "githubStars": null
      },
      "description": "The spec-driven maturation of the Ralph loop: each fresh-context iteration reads PLAN.md, implements the highest-priority unchecked item, checks it off, and commits — so the spec file evolves alongside the codebase.",
      "prompt": "Ralph variant where the loop prompt is \"read PLAN.md, pick highest-priority unchecked item, implement, check it off, commit, exit\" — spec file evolves with the codebase.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: Ralph-style autonomous grinding where you want the plan itself to be the living artifact — a checklist the loop consumes and the team can read, edit, and reprioritize between iterations. How it works: each fresh-context iteration reads PLAN.md, picks the highest-priority unchecked item, implements it, checks it off, commits, and exits. The spec file evolves alongside the codebase: completed items accumulate as history, and anyone can insert, reorder, or annotate items to steer the next iteration without touching the loop machinery. HumanLayer describes this as the spec-driven maturation of the original Ralph. Safety: the checkbox protocol is the state rail — progress is legible in one file, and a human can pause the loop, edit PLAN.md, and resume with redirected priorities. Keep items small and independently shippable, run it on a branch, and add an iteration cap since the loop itself does not carry one.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "HumanLayer",
        "url": "https://www.humanlayer.dev/blog/brief-history-of-ralph"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "deploy-poll-loop",
      "title": "Deploy-poll loop",
      "url": "https://looprepo.dev/loops/deploy-poll-loop",
      "loopType": "loop",
      "category": "devops",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Claude Directory",
        "authority": 80,
        "githubStars": null
      },
      "description": "A hands-free ops loop that polls your deploy every two minutes, runs the smoke test the moment it goes live, and stops with a report if any check fails.",
      "prompt": "/loop every 2 minutes: check deploy status; when it's live, run the smoke test and summarize; if smoke test fails, report the failing check and stop",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you have kicked off a deploy and the next twenty minutes are otherwise dead time — waiting to see it go live, then remembering to run the smoke test against it. How it works: every two minutes the loop checks deploy status. The moment the deploy is live it runs the smoke test and summarizes the results; if the smoke test fails, it reports the failing check and stops rather than continuing to poll or attempting fixes. Safety: the stop-on-failure clause is the notable rail — a failed smoke test halts the loop with a report, leaving the response decision (rollback, hotfix, investigate) to you instead of the loop improvising remediation against production. Everything it does is read-and-report: status checks and test runs, no code or infrastructure changes. It is cheap at a two-minute cadence, but kill it once the deploy is confirmed rather than leaving it polling.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Claude Directory blog",
        "url": "https://www.claudedirectory.org/blog/claude-code-loop-guide"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "claude-progress-txt-harness-pattern-anthropic",
      "title": "claude-progress.txt harness pattern (Anthropic)",
      "url": "https://looprepo.dev/loops/claude-progress-txt-harness-pattern-anthropic",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "official",
        "label": "Anthropic",
        "authority": 100,
        "githubStars": null
      },
      "description": "Anthropic's first-party file-as-memory harness for long-running agents: every fresh-context session recovers state from a progress file and the git log, does one unit of work, updates the file, commits, and exits.",
      "prompt": "Long-running agent harness: each fresh-context session starts by reading `claude-progress.txt` + git log to recover state, does one unit of work, updates the progress file, commits, exits. Initializer session sets up the file; coder sessions loop.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: agent work too long for one session — multi-day builds where context will be lost repeatedly and the question becomes how each new session knows where things stand. This is Anthropic's first-party answer. How it works: every fresh-context session begins by reading claude-progress.txt plus the git log to recover state, does one unit of work, updates the progress file, commits, and exits. An initializer session sets up the progress file; coder sessions then loop the pattern indefinitely. The progress file is curated state — what is done, what is next, what to watch for — while git history is the ground truth it points into. Safety: the discipline lives in the exit ritual: a session that fails to update the progress file before exiting strands the next one, so treat update-then-commit as non-negotiable. One unit of work per session keeps commits reviewable and recovery cheap when an iteration goes sideways.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Anthropic Engineering",
        "url": "https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "architect-builder-cross-vendor-loop",
      "title": "Architect-builder cross-vendor loop",
      "url": "https://looprepo.dev/loops/architect-builder-cross-vendor-loop",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "DanMcInerney/architect-loop",
        "authority": 40,
        "githubStars": null
      },
      "description": "A two-vendor loop that pairs Claude as architect with Codex as builder, using the repo itself as shared memory: the architect writes specs, the builder implements one item per iteration, and the architect reviews the diffs on the next pass.",
      "prompt": "Claude as architect, Codex as builder, the repo as shared memory — architect writes plan/spec files, builder implements one item per iteration, architect reviews diffs next pass.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: tasks where planning quality and implementation throughput are different problems — you want one model doing deliberate architecture and another grinding out code, with a review pass between them. How it works: Claude plays architect, Codex plays builder, and the repo itself is the shared memory. The architect writes plan and spec files into the repo; the builder implements one item per iteration from those specs; on the next pass the architect reviews the resulting diffs and updates the plan. Neither agent holds conversational state about the other — everything they know about each other's work lives in files and git history. Safety: the architect-reviews-diffs step is the built-in check — implementation drift gets caught on the next planning pass rather than accumulating silently. One item per builder iteration keeps changes bounded and attributable. Cap iterations on both sides and keep the spec files small enough that fresh-context reads stay reliable.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "DanMcInerney/architect-loop",
        "url": "https://github.com/DanMcInerney/architect-loop"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "agent-loop-skills-bundle-loop-until-it-s-better",
      "title": "Agent-Loop-Skills bundle — loop until it's better",
      "url": "https://looprepo.dev/loops/agent-loop-skills-bundle-loop-until-it-s-better",
      "loopType": "ralph",
      "category": "quality",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "gaasher/Agent-Loop-Skills",
        "authority": 40,
        "githubStars": null
      },
      "description": "Six verification-gated loops in one open-standard skill bundle — autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, and red-teaming — portable across Claude Code, Codex, and Cursor. Use the red-teaming loop only against systems you own and are authorized to test.",
      "prompt": "\"Loop until it's better\" — verification-gated loops for autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming, packaged as open-standard Agent Skills portable across Claude Code, Codex, Cursor.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want verification-gated looping across more domains than code — the bundle covers autoresearch, scientific writing, data analysis, code, SQL, and prompt optimization, plus red-teaming, in one install. How it works: six loops packaged as open-standard Agent Skills, portable across Claude Code, Codex, and Cursor. Each follows the same loop-until-it-is-better contract: iterate, check the result against a verification gate, and continue only while the gate says the artifact genuinely improved — the same anti-self-grading structure applied per domain. Safety: verification gates are the common rail across all six loops. The red-teaming loop carries its own explicit boundary: use it only against systems you own and are authorized to test — pointing an autonomous adversarial loop at anything else is out of bounds regardless of intent. As with any skill bundle, read each skill before first run and apply your own iteration caps around it.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "gaasher/Agent-Loop-Skills",
        "url": "https://github.com/gaasher/Agent-Loop-Skills"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "autoloop-metric-driven-optimization-loops",
      "title": "AutoLoop — metric-driven optimization loops",
      "url": "https://looprepo.dev/loops/autoloop-metric-driven-optimization-loops",
      "loopType": "ralph",
      "category": "performance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "armgabrielyan/autoloop",
        "authority": 40,
        "githubStars": null
      },
      "description": "Agent-agnostic hill-climbing loops inspired by Karpathy's autoresearch: define a metric, let the agent propose a change, measure, keep it only if the number improved, and repeat.",
      "prompt": "Iterative optimization loops (inspired by Karpathy's autoresearch): define a metric, agent proposes change, harness measures, keep if improved, repeat. Works with Claude Code, Codex, Cursor, Gemini CLI.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: optimization problems with a measurable number — latency, benchmark score, model accuracy, query cost — where you want hill-climbing automated rather than hand-tuned. Inspired by Karpathy's autoresearch pattern. How it works: you define a metric; each iteration the agent proposes a change, the harness measures the metric, and the change is kept only if the number improved — otherwise it is discarded — then the cycle repeats. The keep-only-if-improved rule makes progress monotonic by construction, and because the harness does the measuring, the agent cannot grade its own work. It is agent-agnostic: Claude Code, Codex, Cursor, or Gemini CLI. Safety: measurement-gated acceptance is the rail — no change survives on plausibility alone. The classic residual risk is metric gaming, where the number improves while something unmeasured degrades, so pair the target metric with guard checks (tests still pass, correctness holds) and cap total iterations to bound spend.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "armgabrielyan/autoloop",
        "url": "https://github.com/armgabrielyan/autoloop"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "multi-repo-autonomous-dev-team-loop",
      "title": "Multi-repo autonomous dev team loop",
      "url": "https://looprepo.dev/loops/multi-repo-autonomous-dev-team-loop",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "nexu-io/looper",
        "authority": 40,
        "githubStars": null
      },
      "description": "The fleet pattern: run agent loops across multiple repos in parallel, each isolated in its own git worktree, with a pluggable vendor layer spanning Claude Code, Codex, Cursor CLI, and OpenCode.",
      "prompt": "Register repos, run loops across them in parallel, each loop in its own git worktree; pluggable vendor layer (claude-code, codex, cursor-cli, opencode) — plan, review, fix, ship on a loop.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you are past single-repo loops and want agent capacity across a portfolio — several services or projects receiving loop attention in parallel, the fleet pattern. How it works: register your repos with the runner, then launch loops across them in parallel, each loop isolated in its own git worktree so concurrent runs never trample each other's working state. A pluggable vendor layer means each loop can run on Claude Code, Codex, Cursor CLI, or OpenCode, and the loop shape covers plan, review, fix, and ship. Safety: worktree isolation is the core rail — parallel agents share nothing at the filesystem level, so one loop's mess cannot corrupt another's checkout. The risk that scales with the fleet is spend and review load: five parallel loops produce five streams of diffs needing human eyes. Start with one or two repos and per-loop caps before going wide.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "nexu-io/looper",
        "url": "https://github.com/nexu-io/looper"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "deterministic-backlog-loop-for-codex-cli",
      "title": "Deterministic backlog loop for Codex CLI",
      "url": "https://looprepo.dev/loops/deterministic-backlog-loop-for-codex-cli",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "nibzard/looper",
        "authority": 40,
        "githubStars": null
      },
      "description": "A Codex-first autonomous runner that pulls exactly one task per iteration from a JSON backlog with fresh context each run and a JSONL audit log for full traceability.",
      "prompt": "Autonomous runner: exactly one task per iteration pulled from a JSON backlog, fresh context each run, JSONL audit log for traceability; optional Claude Code interleaving.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want Ralph-style backlog grinding with Codex CLI as the engine, in contexts where traceability matters — you need to answer what the loop did on iteration 14 after the fact. How it works: an autonomous runner that pulls exactly one task per iteration from a JSON backlog, runs it with fresh context, and appends a JSONL audit log entry per iteration, giving the whole run a machine-readable paper trail. The one-task-per-iteration discipline keeps each run bounded and attributable, and the JSON backlog is the shared state between iterations. It can optionally interleave Claude Code runs alongside Codex. Safety: the JSONL audit log is the distinguishing rail — full traceability of what ran, when, and against which task, which most homemade Ralph loops lack entirely. Keep backlog items small and independently shippable, and bound total iterations yourself, since the runner's determinism governs task selection, not spend.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "nibzard/looper",
        "url": "https://github.com/nibzard/looper"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "looper-design-review-your-loop-before-running-it",
      "title": "Looper — design-review your loop before running it",
      "url": "https://looprepo.dev/loops/looper-design-review-your-loop-before-running-it",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "ksimback/looper",
        "authority": 40,
        "githubStars": null
      },
      "description": "A plan-the-loop-first skill: it interviews you about the automation idea, previews the flow as ASCII art, and only writes final loop artifacts after you confirm — a safe on-ramp for loop beginners.",
      "prompt": "Skill interviews you about the automation idea, writes loop artifacts to `looper-output/`, shows an ASCII flow preview, and only finalizes after you confirm — design the loop before any runner touches files.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you are new to loops, or about to run one complex enough that a design mistake is expensive — this is the plan-first on-ramp that front-loads the thinking before any runner touches files. How it works: the skill interviews you about the automation idea, asking the questions a loop design needs answered, then writes the loop artifacts to looper-output/ and shows you an ASCII flow preview of what the loop will actually do. Nothing is finalized until you explicitly confirm — design the loop, inspect it, then run it, as separate steps. Safety: confirmation-before-finalize is the structural rail: the skill produces no final artifacts and runs nothing until you approve the previewed design, so the worst case of a bad interview is a discarded draft in looper-output/. The preview step catches the wrong loop shape before it costs tokens. The eventual run still needs its own caps.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "ksimback/looper",
        "url": "https://github.com/ksimback/looper"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "verification-gated-self-running-loop-skill",
      "title": "Verification-gated self-running loop skill",
      "url": "https://looprepo.dev/loops/verification-gated-self-running-loop-skill",
      "loopType": "ralph",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "selmakcby/loop-engineering",
        "authority": 40,
        "githubStars": null
      },
      "description": "A drop-in Claude Code skill that keeps looping until an external verifier passes — not the model's own self-report — making it a strong anti-reward-hacking pattern for autonomous coding.",
      "prompt": "Drop-in Claude Code skill: self-running agent loop with a \"real, un-foolable verification gate\" — loop continues until an external verifier (not the model's self-report) passes.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: any autonomous loop where you have been burned by the agent declaring victory prematurely — the model reporting done while the actual checks fail is the classic reward-hacking failure of self-directed loops. How it works: a drop-in Claude Code skill implementing a self-running loop whose continuation logic is gated by a real, un-foolable verification step: the loop continues until an external verifier passes, not until the model's self-report says things look good. The verifier is code the model cannot argue with — tests, builds, whatever objective check you wire in — which structurally removes the incentive to describe success instead of achieving it. Safety: the external-verifier gate is the anti-reward-hacking rail and the entire design point. Its guarantee is exactly as strong as the verifier you supply, so invest in that check; a weak verifier resurrects the original problem one level down. Add an iteration cap alongside it.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "selmakcby/loop-engineering",
        "url": "https://github.com/selmakcby/loop-engineering"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "boris-cherny-loop-methodology-agent-loop-skill",
      "title": "Boris Cherny loop methodology + agent-loop skill",
      "url": "https://looprepo.dev/loops/boris-cherny-loop-methodology-agent-loop-skill",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "cocodedk/loop-engineering",
        "authority": 40,
        "githubStars": null
      },
      "description": "A fact-checked knowledge base of Claude Code creator Boris Cherny's loop methodology, packaged as a runnable agent-loop skill you can drop straight into Claude Code.",
      "prompt": "Fact-checked knowledge base of Cherny's loop methodology for running Claude Code, shipped as a runnable `agent-loop` skill in `skill/agent-loop/`.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want to learn or standardize on loop practice from the source — Boris Cherny created Claude Code, and this packages his loop methodology in runnable form rather than as scattered posts. How it works: a fact-checked knowledge base of Cherny's methodology for running Claude Code in loops, shipped with a runnable agent-loop skill in skill/agent-loop/ that you can drop straight into Claude Code and invoke. The knowledge-base half explains the reasoning; the skill half executes the pattern, so the methodology and its implementation stay in sync. Safety: fact-checked is the notable attribute — loop advice attributed to Cherny circulates widely with varying accuracy, and this repo's stated purpose is verifying claims before packaging them. Still treat the skill like any third-party skill: read what it does before running it, and apply your own turn caps and branch discipline around it.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "cocodedk/loop-engineering",
        "url": "https://github.com/cocodedk/loop-engineering"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "loop-init-loop-audit-loop-cost-cli-patterns",
      "title": "loop-init, loop-audit, loop-cost CLI patterns",
      "url": "https://looprepo.dev/loops/loop-init-loop-audit-loop-cost-cli-patterns",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "cobusgreyling/loop-engineering",
        "authority": 40,
        "githubStars": null
      },
      "description": "Three starter CLI tools that turn loop design into a repeatable workflow: scaffold a loop with a goal, budget, and verify step; audit an existing loop design; and estimate cost before you run.",
      "prompt": "Starter CLI tools: `loop-init` scaffolds a loop (goal, budget, verify step), `loop-audit` reviews an existing loop design, `loop-cost` estimates spend before running.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you or your team are designing loops often enough that ad-hoc prompt-writing is producing inconsistent quality, and you want loop design to be a repeatable workflow with a checklist. How it works: three starter CLI tools cover the lifecycle. loop-init scaffolds a new loop with the three elements every good one needs — a goal, a budget, and a verify step — so none get forgotten. loop-audit reviews an existing loop design against those same criteria. loop-cost estimates spend before you run, turning the budget conversation into a pre-flight check rather than a post-mortem. Safety: the value is process discipline rather than runtime enforcement — scaffolded budgets and pre-run cost estimates only protect you if the loop that actually runs honors them. Use these tools to design the loop, then carry the caps into the runner (turn limits, budget ceilings) where they are actually enforced.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "cobusgreyling/loop-engineering",
        "url": "https://github.com/cobusgreyling/loop-engineering"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "claude-loop-iterative-sessions-with-cost-tracking",
      "title": "claude-loop — iterative sessions with cost tracking",
      "url": "https://looprepo.dev/loops/claude-loop-iterative-sessions-with-cost-tracking",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "li0nel/claude-loop",
        "authority": 40,
        "githubStars": null
      },
      "description": "An automation harness that runs repeated Claude Code sessions while tracking cost and tokens per iteration — the reference answer to the number-one objection to agent loops: runaway spend.",
      "prompt": "Automation toolkit running repeated `claude` sessions with per-iteration cost and token monitoring; inspired by Dex Horthy's context-engineering talk.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you are sold on iterative agent sessions but not on surprise bills — this harness exists specifically to answer the number-one objection to agent loops, runaway spend. Inspired by Dex Horthy's context-engineering talk. How it works: an automation toolkit that runs repeated claude sessions in a loop while recording cost and token usage per iteration, so you can see exactly what each cycle consumed rather than discovering the total afterward. The per-iteration granularity is what makes the data actionable: an iteration whose token count spikes is visible immediately, and trends across a run tell you whether the loop is converging or thrashing. Safety: measurement is the rail here — per-iteration cost visibility is what lets you set informed caps and kill a run that is trending wrong. Pair it with hard limits (iteration caps, budget ceilings), since tracking alone observes spend rather than stopping it.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "li0nel/claude-loop",
        "url": "https://github.com/li0nel/claude-loop"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "continuous-claude-pr-gated-ralph-loop",
      "title": "Continuous Claude — PR-gated Ralph loop",
      "url": "https://looprepo.dev/loops/continuous-claude-pr-gated-ralph-loop",
      "loopType": "ralph",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "AnandChowdhary/continuous-claude",
        "authority": 40,
        "githubStars": null
      },
      "description": "The Ralph loop for teams: every iteration ships as a pull request that must pass CI before merging, giving each cycle a verifiable checkpoint. Keep branch protection and human PR approval enabled rather than letting it auto-merge to main unattended.",
      "prompt": "Run Claude Code in a continuous loop that opens a PR per iteration, waits for CI checks, and merges when green, then starts the next iteration.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: running a Ralph-style loop inside a team codebase, where unreviewed commits landing on a shared branch is unacceptable — this variant makes every iteration legible to normal team process. How it works: Claude Code runs in a continuous loop where each iteration opens a pull request, waits for CI checks, merges when green, and then starts the next iteration. The PR-per-iteration structure gives every cycle a verifiable checkpoint: CI is the objective gate, and the PR trail is the audit log of what the loop did and when. Safety: the recommended configuration is to keep branch protection and human PR approval enabled rather than letting the loop auto-merge to main unattended — CI-green means the checks passed, not that the change is wanted. With approval required, the loop becomes a proposal generator; without it, you have effectively granted an agent merge rights to main.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "AnandChowdhary/continuous-claude",
        "url": "https://github.com/AnandChowdhary/continuous-claude"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-with-circuit-breaker-exit-detection",
      "title": "Ralph with circuit-breaker exit detection",
      "url": "https://looprepo.dev/loops/ralph-with-circuit-breaker-exit-detection",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "frankbria/ralph-claude-code",
        "authority": 40,
        "githubStars": null
      },
      "description": "A safe Ralph variant that solves runaway loops with circuit-breaker heuristics: it halts automatically when iterations stop producing file changes or keep hitting the same error.",
      "prompt": "Ralph loop wrapped with exit heuristics: no file changes for 3 consecutive iterations = no progress → stop; same error 5 consecutive loops = stuck → stop.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: unattended Ralph runs where the failure mode that scares you is the runaway — a loop that spins for hours making no progress or repeating the same error while the bill grows. How it works: a standard Ralph loop wrapped with two exit heuristics that watch the loop from outside. No file changes for three consecutive iterations means no progress is being made, so it stops. The same error appearing five consecutive loops means the agent is stuck, so it stops. Both are cheap, observable signals that need no model judgment to evaluate. Safety: the circuit breakers are the whole point — they convert the two classic runaway shapes, idle spinning and error loops, into automatic halts instead of morning surprises. They bound waste rather than damage: the iterations that do run still change files and commit, so the usual sandbox, branch, and review discipline still applies underneath.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "frankbria/ralph-claude-code",
        "url": "https://github.com/frankbria/ralph-claude-code"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "official-ralph-wiggum-plugin-anthropic",
      "title": "Official Ralph Wiggum plugin (Anthropic)",
      "url": "https://looprepo.dev/loops/official-ralph-wiggum-plugin-anthropic",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "official",
        "label": "Anthropic",
        "authority": 100,
        "githubStars": null
      },
      "description": "Anthropic's first-party take on the Ralph loop: a Claude Code plugin that runs the iterate-fresh-context pattern with a managed stop and iteration mechanism built in.",
      "prompt": "Install the `ralph-wiggum` plugin from the anthropics/claude-code repo; it wraps the Ralph loop with a managed stop/iteration mechanism inside Claude Code.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: you want Ralph-style fresh-context iteration but would rather not hand-roll a bash while-loop and its stop logic — this is Anthropic's first-party packaging of the pattern. How it works: install the ralph-wiggum plugin from the anthropics/claude-code repo; it wraps the iterate-with-fresh-context loop inside Claude Code with a managed stop and iteration mechanism built in, so starting, bounding, and ending the loop are handled by the plugin rather than by shell plumbing you maintain yourself. Safety: the managed stop mechanism is the main advantage over the raw bash original, which loops forever by construction — here the halt logic is part of the tool. The usual Ralph rails still apply on top: run it against a repo where commits are cheap to revert, keep the per-iteration task small, and review the accumulated commits rather than trusting a long unattended run blindly.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "anthropics/claude-code",
        "url": "https://github.com/anthropics/claude-code/blob/main/plugins/ralph-wiggum/README.md"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "the-original-ralph-wiggum-loop",
      "title": "The original Ralph Wiggum loop",
      "url": "https://looprepo.dev/loops/the-original-ralph-wiggum-loop",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "The canonical Ralph Wiggum loop by Geoffrey Huntley: a bash while-loop that feeds Claude Code one fresh-context iteration at a time, using the filesystem and git as memory. Run it only in a sandboxed environment with permissions configured — never with permission checks disabled.",
      "prompt": "`while :; do cat PROMPT.md | claude -p ; done` — PROMPT.md holds the spec + \"pick ONE task from the plan, implement, test, commit, exit.\" Fresh context every iteration; filesystem + git = memory.",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "When to use: long-horizon autonomous builds where a single session's context would degrade — you have a spec and a plan and want the agent to grind through it iteration by iteration, possibly overnight. This is the pattern everything else in the Ralph family descends from. How it works: a bash while-loop pipes PROMPT.md into claude -p forever; the prompt tells each run to pick ONE task from the plan, implement it, test it, commit, and exit. Every iteration starts with fresh context, and the filesystem plus git history serve as the only memory between runs. Safety: the while-loop is infinite by construction — there is no built-in stop condition, so supervise it or add your own iteration cap and exit checks. Run it only in a sandboxed environment with permissions properly configured, and never with permission checks disabled; an unattended agent with full permissions is the entire risk surface here.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ci-pipeline-speedup",
      "title": "CI pipeline speedup",
      "url": "https://looprepo.dev/loops/ci-pipeline-speedup",
      "loopType": "goal",
      "category": "ci",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ci",
        "caching",
        "speed"
      ],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Profile the CI pipeline and cut wall-clock time under a target by improving caching, splitting slow jobs, and removing redundant steps, verifying every run stays green.",
      "prompt": "/goal the CI pipeline completes in under 10 minutes on a typical PR — analyze the slowest recent runs with `gh run view`, apply one speedup per turn (better dependency caching, job parallelization, removing duplicated steps, trimming artifacts), push to a test branch, and confirm the workflow still passes; stop at the target or after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "One change per turn makes it obvious which tweak saved (or cost) time. All experiments happen on a test branch, never on main's workflow directly.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "upgrade-node-lts",
      "title": "Upgrade to current Node LTS",
      "url": "https://looprepo.dev/loops/upgrade-node-lts",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "node",
        "lts",
        "upgrade"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Move the project to the current Node LTS across .nvmrc, CI config, Dockerfiles, and engines, fixing deprecations until everything is green on the new runtime.",
      "prompt": "/goal the project runs on the current Node LTS — update .nvmrc, the engines field, CI workflow files, and any Dockerfile base images to the LTS version, then run install, build, lint, and the full test suite on it, fixing deprecation warnings and breakages one at a time; stop when all are green or after 15 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The sneaky failures are usually native modules and CI images, which is why the goal names every file class explicitly. Do it on a branch and let CI confirm.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "memory-leak-hunt",
      "title": "Memory leak hunt",
      "url": "https://looprepo.dev/loops/memory-leak-hunt",
      "loopType": "goal",
      "category": "debugging",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "memory",
        "leak",
        "heap"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Drive a suspected memory leak to ground: reproduce growth under a repeated workload, capture heap snapshots, and fix the retention until memory stays flat.",
      "prompt": "/goal heap usage stays flat (within 5%) across 500 repetitions of the failing workload in the leak-repro script — capture heap snapshots before and after, identify what is being retained and by which reference chain, fix the leak, and re-run the repro to confirm; stop after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Write the smallest repro script you can first; the loop's job is diagnosis and fix, not finding the repro. The flat-heap re-run is the proof.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "commit-message-hygiene",
      "title": "Commit message hygiene on a branch",
      "url": "https://looprepo.dev/loops/commit-message-hygiene",
      "loopType": "goal",
      "category": "git",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "commits",
        "conventional-commits",
        "rebase"
      ],
      "safety": {
        "grade": "A",
        "score": 95
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Rewrite the commit messages on your feature branch to conventional-commit format with meaningful bodies before opening the PR, leaving the code untouched.",
      "prompt": "/goal every commit on this branch (ahead of main) has a conventional-commit subject under 72 characters and a body explaining why — use interactive rebase to reword only (no code changes, no commits dropped), verify with `git log main..HEAD`, and confirm the diff against the original branch tip is empty; stop after 5 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The empty-diff check proves only messages changed. Run before the PR is opened and never on a branch others are already building on.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-bug-backlog",
      "title": "Ralph the bug backlog",
      "url": "https://looprepo.dev/loops/ralph-bug-backlog",
      "loopType": "ralph",
      "category": "debugging",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "bugs",
        "regression-tests"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "Work a triaged bug list one fix per fresh-context iteration: reproduce first, fix minimally, prove it with a regression test, and log root-cause patterns to guardrails.",
      "prompt": "/loop fresh context each iteration: read bugs.json and .ralph/guardrails.md, take the top open bug, write a failing test that reproduces it before touching any code, then apply the smallest fix that makes the test pass with the rest of the suite green, and mark the bug fixed; if you cannot reproduce it, mark it needs-info with your findings instead; append recurring root-cause patterns to .ralph/guardrails.md; stop when bugs.json is clear or after 25 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Reproduce-before-fix is the discipline that separates this from guess-and-patch. The needs-info escape hatch stops it from inventing fixes for phantom bugs.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-docs-backlog",
      "title": "Ralph the docs backlog",
      "url": "https://looprepo.dev/loops/ralph-docs-backlog",
      "loopType": "ralph",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "docs",
        "examples"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "Document one undocumented public module per fresh-context iteration, verifying every code sample compiles and accumulating style rules in guardrails so the docs read like one author wrote them.",
      "prompt": "/loop fresh context each iteration: read docs-backlog.json, docs/STYLE.md, and .ralph/guardrails.md; pick the top undocumented module, write its reference page with a runnable example, execute the example to prove it works, and mark the module done; add any style or structure decision to .ralph/guardrails.md; stop when the backlog is empty or after 20 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Executing every example is the anti-hallucination guarantee — docs written this way cannot describe an API that does not exist. Seed docs/STYLE.md with a page you already like.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-refactor-backlog",
      "title": "Ralph a refactor, module by module",
      "url": "https://looprepo.dev/loops/ralph-refactor-backlog",
      "loopType": "ralph",
      "category": "refactoring",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "refactor",
        "consistency"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "Break a large refactor into a JSON backlog of modules and let fresh-context iterations convert one module per pass, with guardrails capturing every pattern decision so the result stays consistent.",
      "prompt": "/loop fresh context each iteration: read refactor-plan.json and .ralph/guardrails.md, take the next module not marked converted, migrate it to the target pattern described in PROMPT.md, run tests and typecheck, and mark it converted only when green; record every convention decision you make (naming, file layout, error handling) in .ralph/guardrails.md so later modules match earlier ones; stop when all modules are converted or after 30 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The guardrails file is what keeps module 27 stylistically identical to module 2 despite each iteration knowing nothing about the last. Review it after the first few passes and correct any convention you dislike early.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-test-backlog",
      "title": "Ralph a test backlog",
      "url": "https://looprepo.dev/loops/ralph-test-backlog",
      "loopType": "ralph",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "tests",
        "coverage"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "Iterate over a prioritized list of untested modules with fresh context each pass, writing real behavioral tests for one module at a time and banking lessons in a guardrails file.",
      "prompt": "/loop each iteration with fresh context: read .ralph/test-backlog.json and .ralph/guardrails.md, pick the top unfinished module, write behavioral tests for its public API (no snapshot-only tests), run the suite, and mark the module done only when its tests pass and coverage for it exceeds 80%; append any discovered testing gotcha (fixtures, mocking rules, async traps) to .ralph/guardrails.md; stop when the backlog is empty or after 25 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Generate the backlog from your coverage report, worst-covered first. The guardrails file quickly accumulates project-specific mocking rules that make later iterations noticeably better.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-prd-backlog",
      "title": "Ralph the PRD backlog",
      "url": "https://looprepo.dev/loops/ralph-prd-backlog",
      "loopType": "ralph",
      "category": "planning",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "prd",
        "backlog"
      ],
      "safety": {
        "grade": "A",
        "score": 95
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "The canonical Ralph loop: each iteration starts fresh, reads the PRD and guardrails, ships exactly one backlog item end-to-end, and records what it learned.",
      "prompt": "/loop start each iteration with fresh context: read PROMPT.md, prd.json, and .ralph/guardrails.md; pick the single highest-priority item in prd.json not marked done, implement it with tests, run the full check suite, commit and mark it done only if green; if blocked or a check fails twice the same way, append the lesson to .ralph/guardrails.md and move on; stop when every item is done or after 30 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Write prd.json as small, independently-shippable items — Ralph lives or dies on backlog granularity. Fresh context per iteration prevents long-session drift.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "stale-branch-report",
      "title": "Stale branch report",
      "url": "https://looprepo.dev/loops/stale-branch-report",
      "loopType": "schedule",
      "category": "git",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "branches",
        "cleanup",
        "hygiene"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Every Monday, list remote branches with no commits in 30 days, classify each as merged, abandoned, or unclear, and file a cleanup checklist issue — deleting nothing.",
      "prompt": "/schedule every Monday at 9am, list remote branches with no commits in the last 30 days; for each, note whether it is fully merged into main, who last touched it, and any open PR; post the list as a checklist in a single `branch-cleanup` issue, and do not delete any branch yourself",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Humans check the boxes and do the deleting; the loop just does the archaeology. Rotate the issue rather than opening a new one weekly.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "weekly-tech-debt-report",
      "title": "Weekly tech debt report",
      "url": "https://looprepo.dev/loops/weekly-tech-debt-report",
      "loopType": "schedule",
      "category": "maintenance",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "debt",
        "metrics",
        "report"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Every Friday, compile a trend report of debt signals — TODO count, lint suppressions, type coverage, largest files — so the team sees drift before it compounds.",
      "prompt": "/schedule every Friday at 4pm, measure TODO/FIXME count, eslint-disable and ts-ignore counts, type coverage, and the five largest source files; append the numbers with week-over-week deltas to reports/tech-debt.md and call out the single worst trend in one paragraph",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Read-only and cheap to run. The week-over-week deltas are the value; absolute numbers alone rarely change behavior.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "readme-freshness-check",
      "title": "README freshness check",
      "url": "https://looprepo.dev/loops/readme-freshness-check",
      "loopType": "schedule",
      "category": "docs",
      "difficulty": "beginner",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "readme",
        "docs",
        "freshness"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Once a week, verify every command, path, and badge in the README actually works against the current codebase and open a PR fixing anything stale.",
      "prompt": "/schedule every Friday at 3pm, verify the README: run each documented setup and usage command in a clean checkout, check that referenced files and scripts exist, and open a PR correcting anything that fails or has drifted, with a note explaining each fix",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "READMEs rot fastest right after big refactors, so this pays for itself in active repos. All changes arrive as a reviewable PR.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "issue-dedup-schedule",
      "title": "Issue de-duplication sweep",
      "url": "https://looprepo.dev/loops/issue-dedup-schedule",
      "loopType": "schedule",
      "category": "planning",
      "difficulty": "beginner",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [
        "issues",
        "duplicates",
        "github"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Twice a week, scan new GitHub issues for duplicates of existing ones and link them with a polite comment and a duplicate label, closing nothing automatically.",
      "prompt": "/schedule every Tuesday and Friday at 10am, compare issues opened in the last 4 days against existing open issues; when one is a likely duplicate, comment with a link to the original and apply the `possible-duplicate` label, but never close anything yourself",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The never-close rule matters: false-positive closures burn goodwill with reporters, while a label plus link costs nothing when wrong.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "nightly-e2e-run",
      "title": "Nightly e2e run with morning report",
      "url": "https://looprepo.dev/loops/nightly-e2e-run",
      "loopType": "schedule",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "e2e",
        "nightly",
        "playwright"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Run the full end-to-end suite every night at 2am and wake up to a digest of failures with screenshots, suspect commits, and a flakiness verdict per test.",
      "prompt": "/schedule every day at 2am, run the full e2e suite against the staging build; for each failure, attach the trace or screenshot, list the commits since the last green run, and say whether the failure looks flaky or real; post the digest to e2e-reports/ as a dated markdown file",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Nightly cadence catches integration breakage without slowing daytime CI. The flaky-or-real verdict is the part that saves you triage time each morning.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "weekly-dependency-audit",
      "title": "Weekly dependency vulnerability audit",
      "url": "https://looprepo.dev/loops/weekly-dependency-audit",
      "loopType": "schedule",
      "category": "security",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "audit",
        "vulnerabilities",
        "weekly"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Every Monday morning, run the dependency vulnerability audit, open one PR fixing what auto-fix can handle safely, and file issues for the rest.",
      "prompt": "/schedule every Monday at 8am, run `npm audit`, open a single PR applying only non-breaking fixes with tests passing, and file one issue per remaining high or critical advisory with its CVE link and affected paths",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Splitting auto-fixable from breaking changes keeps the weekly PR trivially mergeable. Issues give the breaking upgrades a paper trail.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "changelog-from-commits",
      "title": "Changelog generation from commits",
      "url": "https://looprepo.dev/loops/changelog-from-commits",
      "loopType": "goal",
      "category": "docs",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "changelog",
        "release",
        "commits"
      ],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Turn the commit history since the last release tag into a human-readable, categorized CHANGELOG entry ready for the next version.",
      "prompt": "/goal CHANGELOG.md has a complete entry for the next release — read every commit since the last version tag, group changes into Added, Changed, Fixed, and Removed, write user-facing descriptions (not commit messages), link PR numbers, and flag anything that looks like a breaking change; stop after 5 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Quality depends on your commit hygiene; pairs well with the commit-message loops elsewhere in this directory. Always read the breaking-change flags before publishing.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "secrets-scan-clean",
      "title": "Secrets scan until clean",
      "url": "https://looprepo.dev/loops/secrets-scan-clean",
      "loopType": "goal",
      "category": "security",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "secrets",
        "gitleaks",
        "credentials"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Run a secrets scanner over the working tree and drive the findings to zero: real secrets get flagged for rotation, false positives get baselined.",
      "prompt": "/goal `gitleaks detect --no-git` reports zero findings — for each finding, tell me whether it looks like a real credential (flag it for rotation and replace it with an env var lookup) or a false positive (add it to the baseline with a comment); never print the secret value itself; stop after 8 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Rotation itself stays human-owned: the loop replaces and flags but never sees rotation flows. The never-print rule keeps credentials out of the transcript.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "api-contract-tests",
      "title": "API contract test backfill",
      "url": "https://looprepo.dev/loops/api-contract-tests",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "openapi",
        "contract-tests",
        "api"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Generate a contract test for every documented endpoint in the OpenAPI spec so the spec and the implementation can never silently drift.",
      "prompt": "/goal every path in openapi.yaml has a contract test asserting its status codes and response schema — add tests for one untested endpoint per turn, run the suite, and fix either the spec or the handler when they disagree (tell me which you chose); stop when all paths are covered or after 15 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The interesting output is the disagreements: each one is a real spec-vs-implementation bug. Make sure it reports which side it corrected.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "docker-image-slimming",
      "title": "Docker image slimming",
      "url": "https://looprepo.dev/loops/docker-image-slimming",
      "loopType": "goal",
      "category": "devops",
      "difficulty": "intermediate",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "docker",
        "image-size",
        "containers"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Iteratively shrink a Docker image under a size target using multi-stage builds, smaller base images, and layer cleanup, verifying the container still boots each turn.",
      "prompt": "/goal `docker images` shows the app image under 300 MB — apply one slimming change per turn (multi-stage build, slimmer base image, prune build deps, consolidate layers), rebuild, and verify the container starts and passes its healthcheck before the next change; stop at the target or after 8 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The boot-and-healthcheck verification is essential; slim images that fail at runtime are worse than fat ones. Set a target that suits your stack.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "bundle-size-budget",
      "title": "Bundle size budget",
      "url": "https://looprepo.dev/loops/bundle-size-budget",
      "loopType": "goal",
      "category": "performance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "bundle",
        "webpack",
        "performance"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Shrink the production JavaScript bundle under a hard budget by attacking the largest modules with code-splitting, lighter imports, and dead-weight removal.",
      "prompt": "/goal the main production bundle is under 250 KB gzipped — run the build with the bundle analyzer, address the single largest contributor each turn (code-split it, replace it with a lighter import, or drop it), and confirm the build and tests stay green; stop at the budget or after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Largest-contributor-first gives the steepest wins early. Set the budget to your real target and keep the analyzer output in each turn's report.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "n-plus-one-query-hunt",
      "title": "N+1 query hunt",
      "url": "https://looprepo.dev/loops/n-plus-one-query-hunt",
      "loopType": "goal",
      "category": "database",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "n+1",
        "orm",
        "queries"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Instrument the test suite with query logging, find endpoints issuing N+1 queries, and fix them with eager loading or batching until the hot paths are clean.",
      "prompt": "/goal no endpoint in the integration test suite issues more than 10 SQL queries per request — enable query logging in the test environment, find the worst N+1 offender, fix it with eager loading or a batched query, verify the count dropped and tests still pass, then move to the next; stop after 12 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Tune the query budget to your app. Verifying the count actually dropped each turn prevents fixes that just move the problem.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "dependency-upgrade-one-at-a-time",
      "title": "Upgrade dependencies one at a time",
      "url": "https://looprepo.dev/loops/dependency-upgrade-one-at-a-time",
      "loopType": "goal",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "dependencies",
        "upgrades",
        "npm"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Walk through outdated dependencies one package per turn, upgrading, running the full check suite, and pinning back anything that breaks.",
      "prompt": "/goal `npm outdated` lists no minor or patch updates — upgrade exactly one package per turn, run tests, lint, and build after each, commit if green, and pin the previous version with a note in UPGRADE-BLOCKERS.md if it fails; stop after 20 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "One-at-a-time means every breakage is attributable to a single package. Major versions are deliberately excluded; handle those individually with their changelogs.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "dead-code-elimination",
      "title": "Dead code elimination",
      "url": "https://looprepo.dev/loops/dead-code-elimination",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "dead-code",
        "knip",
        "cleanup"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Hunt down unreferenced exports, unused files, and unreachable branches, deleting them in small verified steps until the analyzer reports clean.",
      "prompt": "/goal `npx knip` reports no unused files or exports — remove one cluster of dead code at a time, run the full test suite and typecheck after each removal, and revert any deletion that breaks them; stop after 15 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The delete-verify-revert rhythm makes this safe on codebases with good test coverage; be more cautious on repos with reflection or dynamic imports.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "config-drift-check",
      "title": "Config drift check",
      "url": "https://looprepo.dev/loops/config-drift-check",
      "loopType": "loop",
      "category": "devops",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "config",
        "drift",
        "environments"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Compare environment config files and example templates every hour and report keys that exist in one environment but not the others.",
      "prompt": "/loop 60m diff the keys (not values) across .env.example, config/staging.yaml, and config/production.yaml; report any key present in one file but missing in another, and any key in .env.example that no code references anymore",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Compares key names only, never secret values, so nothing sensitive enters the transcript. Catches the classic works-in-staging-missing-in-prod config bug early.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "benchmark-regression-watch",
      "title": "Benchmark regression watch",
      "url": "https://looprepo.dev/loops/benchmark-regression-watch",
      "loopType": "loop",
      "category": "performance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "benchmarks",
        "regression",
        "performance"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Run the benchmark suite every 30 minutes during active development and raise a flag the moment any benchmark slips more than 5 percent from baseline.",
      "prompt": "/loop 30m run `npm run bench`, compare each result to the baselines in bench/baseline.json, and if any benchmark regressed more than 5%, show me the numbers and the commits since the last clean run",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Commit a baseline file first so comparisons are stable. Report-only, which makes it safe; pair with a bisect goal loop when it catches something.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "todo-burn-down",
      "title": "TODO burn-down",
      "url": "https://looprepo.dev/loops/todo-burn-down",
      "loopType": "loop",
      "category": "maintenance",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "todo",
        "debt",
        "cleanup"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Chip away at the oldest TODO comments in the codebase, one per pass: either resolve it properly or convert it into a tracked issue.",
      "prompt": "/loop 30m find the oldest TODO or FIXME comment in the codebase, and either implement it (with a test) if it takes under 50 changed lines, or open a GitHub issue capturing its context and delete the comment; report which TODO you handled; stop when none remain",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The 50-line ceiling keeps each pass reviewable. Old TODOs often encode forgotten constraints, so skim its reports before merging.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "rebase-train-conductor",
      "title": "Rebase train conductor",
      "url": "https://looprepo.dev/loops/rebase-train-conductor",
      "loopType": "loop",
      "category": "git",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "rebase",
        "stacked-prs",
        "git"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Keep a stack of feature branches rebased in order as their parents merge, resolving trivial conflicts and flagging risky ones for a human.",
      "prompt": "/loop 15m for each branch listed in .rebase-train (in order), rebase it onto its updated parent, resolve only trivial conflicts (imports, formatting, lockfiles), run the test suite, and push with `--force-with-lease`; if a conflict touches logic, stop that branch and leave a summary comment on its PR instead",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "List branches bottom-up in .rebase-train. Uses --force-with-lease on feature branches only; it never touches main, and logic conflicts always go to a human.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "sentry-error-triage-loop",
      "title": "Sentry error triage loop",
      "url": "https://looprepo.dev/loops/sentry-error-triage-loop",
      "loopType": "loop",
      "category": "debugging",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [
        "sentry",
        "errors",
        "triage"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Every 30 minutes, pull the newest unresolved Sentry issues, match each stack trace to the code, and draft a root-cause note and suggested fix per issue.",
      "prompt": "/loop 30m list the newest unresolved Sentry issues for this project, and for each new one: locate the stack trace in the codebase, write a short root-cause hypothesis and suggested fix as a comment on the issue, and flag anything that looks like a regression from the last release",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Requires Sentry access via MCP or CLI token. It comments and hypothesizes but does not change code, keeping it safe to run against production error streams.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "flaky-ci-quarantine-watch",
      "title": "Flaky CI quarantine watch",
      "url": "https://looprepo.dev/loops/flaky-ci-quarantine-watch",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "flaky",
        "ci",
        "quarantine"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "curated",
        "label": "looprepo",
        "authority": 60,
        "githubStars": null
      },
      "description": "Watch CI runs on main every 20 minutes and quarantine any test that fails then passes on retry, filing an issue for each one it benches.",
      "prompt": "/loop 20m check the last CI runs on main with `gh run list`; if a test failed and then passed on retry, mark it skipped with a link to a new tracking issue you open via `gh issue create`, and report what you quarantined",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Quarantining beats letting flakes erode trust in CI, but review the skip list weekly so tests actually get fixed. Needs gh authenticated with issue-create permission.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "looprepo",
        "url": "https://looprepo.dev"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ralph-guardrails-learning",
      "title": "Guardrails that learn from failure",
      "url": "https://looprepo.dev/loops/ralph-guardrails-learning",
      "loopType": "ralph",
      "category": "automation",
      "difficulty": "advanced",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "ralph",
        "guardrails",
        "self-improving"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "notable",
        "label": "Geoffrey Huntley",
        "authority": 80,
        "githubStars": null
      },
      "description": "A Ralph-style loop that writes its own rules: when a check fails the same way twice, the failure pattern gets appended to a guardrails file that every later iteration reads first.",
      "prompt": "/loop read .ralph/guardrails.md before doing anything, then run the full check suite and fix the first failure; if a check fails twice with the same error, append the failure pattern and a one-line rule for avoiding it to .ralph/guardrails.md before retrying; stop when all checks pass or after 15 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Create an empty .ralph/guardrails.md first and commit it so learned rules survive across sessions. The file becomes a project-specific playbook of what not to do.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "Geoffrey Huntley (Ralph technique)",
        "url": "https://ghuntley.com/ralph/"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "nested-perfect-loop",
      "title": "The nested perfect loop",
      "url": "https://looprepo.dev/loops/nested-perfect-loop",
      "loopType": "loop",
      "category": "review",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "claude-code"
      ],
      "tags": [
        "nested",
        "review",
        "pr"
      ],
      "safety": {
        "grade": "B",
        "score": 80
      },
      "provenance": {
        "tier": "community",
        "label": "awesome-agent-loops",
        "authority": 40,
        "githubStars": null
      },
      "description": "A loop wrapping a goal wrapping a review: every 30 minutes, drive all PR review comments to resolved via /review, 10 turns max per pass.",
      "prompt": "/loop 30m /goal all PR review comments resolved via /review, stop after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Demonstrates loop composition: the outer timer re-triggers a bounded goal. Kill the outer loop once the PR is approved.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "awesome-agent-loops",
        "url": "https://github.com/serenakeyitan/awesome-agent-loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "keep-docs-in-sync",
      "title": "Keep docs in sync with main",
      "url": "https://looprepo.dev/loops/keep-docs-in-sync",
      "loopType": "schedule",
      "category": "docs",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "docs",
        "drift",
        "automation"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "starmexxx",
        "authority": 40,
        "githubStars": null
      },
      "description": "On every push to main, check whether changed code drifted from the docs in /docs and open a PR fixing anything out of date.",
      "prompt": "/schedule on every push to main, check whether the changed code drifted from the docs in /docs, and open a PR fixing anything out of date",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Because it opens PRs rather than pushing directly, a human always reviews the doc changes. Fires on every push, so cost scales with commit volume.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "starmexxx",
        "url": "https://x.com/starmexxx/status/2044653921629606204"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "morning-issue-triage",
      "title": "Morning issue triage",
      "url": "https://looprepo.dev/loops/morning-issue-triage",
      "loopType": "schedule",
      "category": "planning",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [
        "issues",
        "triage",
        "github"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "chenchengpro",
        "authority": 40,
        "githubStars": null
      },
      "description": "Every weekday at 9am, label new GitHub issues from the last 24 hours by area and priority and post a one-line summary on each.",
      "prompt": "/schedule every weekday at 9am, label new issues from the last 24h by area and priority, and post a one-line summary on each",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Define your label taxonomy in CLAUDE.md so classifications stay consistent. Comments are public, so review the tone it uses for a few days.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "chenchengpro",
        "url": "https://x.com/chenchengpro/status/2044212236881932637"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "format-until-clean",
      "title": "Format until clean",
      "url": "https://looprepo.dev/loops/format-until-clean",
      "loopType": "goal",
      "category": "quality",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "formatting",
        "prettier",
        "cleanup"
      ],
      "safety": {
        "grade": "D",
        "score": 40
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run the formatter, hand-fix anything it can't auto-fix, and repeat until git diff is empty.",
      "prompt": "/goal `npm run format` leaves no diff — run the formatter, hand-fix anything it can't auto-fix, repeat until `git diff` is empty",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The empty-diff exit condition is unambiguous, which makes this one of the safest loops to run unattended.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "apply-db-migrations",
      "title": "Apply database migrations cleanly",
      "url": "https://looprepo.dev/loops/apply-db-migrations",
      "loopType": "goal",
      "category": "database",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "migrations",
        "prisma",
        "schema"
      ],
      "safety": {
        "grade": "B",
        "score": 75
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run migrations, fix schema or SQL errors, and repeat until prisma migrate status reports clean, capped at 6 turns.",
      "prompt": "/goal all database migrations apply cleanly — run them, fix schema or SQL errors, repeat until `npx prisma migrate status` is clean; stop after 6 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Point it at a development database, never production. Prisma-flavored, but the pattern maps to any migration tool with a status command.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "clean-up-the-slop",
      "title": "Clean up the slop",
      "url": "https://looprepo.dev/loops/clean-up-the-slop",
      "loopType": "goal",
      "category": "quality",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "cleanup",
        "lint",
        "diff"
      ],
      "safety": {
        "grade": "A",
        "score": 100
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Review your recent diff for debug code, dead branches, and bad names, then fix with minimal edits until lint and tests pass.",
      "prompt": "/goal the recent diff is clean and convention-aligned — review it for debug code, dead branches, and bad names, fix with minimal edits until `npm run lint && npm test` passes; stop after 4 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Perfect as a final pass after a long agent session. The tight 4-turn cap keeps it from rewriting things it shouldn't.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "get-the-build-green",
      "title": "Get the build green",
      "url": "https://looprepo.dev/loops/get-the-build-green",
      "loopType": "goal",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "build",
        "errors",
        "starter"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run the build, fix the first error, and repeat until npm run build exits 0, with a 10-turn cap.",
      "prompt": "/goal `npm run build` exits 0 — run the build, fix the first error, repeat until it succeeds; stop after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Fix-the-first-error keeps each turn small and verifiable. Works for any build command; substitute your own.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "reach-coverage-target",
      "title": "Reach a coverage target",
      "url": "https://looprepo.dev/loops/reach-coverage-target",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "coverage",
        "tests",
        "quality"
      ],
      "safety": {
        "grade": "C",
        "score": 65
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Add focused tests for the least-covered files and re-measure each turn until coverage hits 80 percent or the turn cap.",
      "prompt": "/goal test coverage is at least 80% with all tests passing — add focused tests for the least-covered files, re-run coverage each turn, stop at the threshold or after 12 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Adjust the threshold to your project. Review the generated tests afterward; coverage loops can produce assertions that pass without proving much.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "ship-pr-until-green",
      "title": "Ship a PR until green",
      "url": "https://looprepo.dev/loops/ship-pr-until-green",
      "loopType": "goal",
      "category": "git",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "pr",
        "ci",
        "github"
      ],
      "safety": {
        "grade": "A",
        "score": 90
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Implement a change, open the PR with gh, then keep fixing CI failures until every check passes, all in one goal loop.",
      "prompt": "/goal a PR is open for this change and every CI check passes — implement it, test locally, push, open the PR with `gh pr create`, then keep fixing failures (re-check with `gh pr checks`) until green; stop after 10 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Run from a feature branch with gh authenticated. The 10-turn cap keeps a stubborn CI failure from becoming an expensive stalemate.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops/ship-pr-until-green"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "migrate-an-api",
      "title": "Migrate an API import by import",
      "url": "https://looprepo.dev/loops/migrate-an-api",
      "loopType": "goal",
      "category": "refactoring",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "migration",
        "refactor",
        "typescript"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "community",
        "label": "KingBootoshi",
        "authority": 40,
        "githubStars": null
      },
      "description": "Sweep a codebase from a legacy API to its v2 replacement with tests and typecheck as the safety net, capped at 30 turns.",
      "prompt": "/goal every file importing from `./legacy-api` now imports from `./v2-api`, all tests pass, and `npm run typecheck` is clean — stop after 30 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Swap the module paths for your own migration. The typecheck condition catches signature drift that tests miss.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "KingBootoshi",
        "url": "https://x.com/KingBootoshi/status/2060068980728184842"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "hit-acceptance-criteria",
      "title": "Hit acceptance criteria",
      "url": "https://looprepo.dev/loops/hit-acceptance-criteria",
      "loopType": "goal",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "medium",
      "agents": [
        "claude-code",
        "codex"
      ],
      "tags": [
        "api",
        "acceptance",
        "feature"
      ],
      "safety": {
        "grade": "B",
        "score": 85
      },
      "provenance": {
        "tier": "community",
        "label": "akshay_pachaar",
        "authority": 40,
        "githubStars": null
      },
      "description": "Drive a feature to done against explicit acceptance criteria: a working paginated endpoint, passing tests, clean lint, and a hard turn cap.",
      "prompt": "/goal the /users endpoint returns 200 with a paginated JSON body, all tests pass, and lint is clean — stop after 20 turns",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Adapt the endpoint and criteria to your ticket. Writing the acceptance criteria into the goal is what makes this reliable.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "akshay_pachaar",
        "url": "https://x.com/akshay_pachaar/status/2055208848609460525"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "fix-tests-and-lint",
      "title": "Fix tests and lint",
      "url": "https://looprepo.dev/loops/fix-tests-and-lint",
      "loopType": "goal",
      "category": "quality",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "tests",
        "lint",
        "starter"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "RodmanAi",
        "authority": 40,
        "githubStars": null
      },
      "description": "The classic one-liner goal loop: iterate until every test passes and the linter reports zero problems.",
      "prompt": "/goal all tests pass and lint is clean",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "The simplest useful goal loop and a great first one to try. Works in any repo with test and lint scripts wired up.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "RodmanAi",
        "url": "https://x.com/RodmanAi/status/2054975035639812170"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "wait-for-ci",
      "title": "Wait for CI so you don't have to",
      "url": "https://looprepo.dev/loops/wait-for-ci",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "ci",
        "github",
        "watcher"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "louiswharmby",
        "authority": 40,
        "githubStars": null
      },
      "description": "Poll gh pr checks every 10 minutes and get told when the PR is ready to merge, or a summary of which checks failed and why.",
      "prompt": "/loop 10m run `gh pr checks 1234`; if all pass, tell me it's ready to merge; if any fail, summarize which and why",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Read-only and cheap. Replace 1234 with your PR number and go do something else.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "louiswharmby",
        "url": "https://x.com/louiswharmby/status/2063962089819869227"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "babysit-many-prs",
      "title": "Babysit many PRs at once",
      "url": "https://looprepo.dev/loops/babysit-many-prs",
      "loopType": "loop",
      "category": "ci",
      "difficulty": "advanced",
      "costRisk": "high",
      "agents": [
        "codex",
        "claude-code"
      ],
      "tags": [
        "pr",
        "ci",
        "automation"
      ],
      "safety": {
        "grade": "C",
        "score": 55
      },
      "provenance": {
        "tier": "community",
        "label": "loops!",
        "authority": 40,
        "githubStars": null
      },
      "description": "Keep every PR labeled codex-watch healthy: fix CI failures, rebase behind-main branches, and nudge pending reviewers on a 15-minute cadence.",
      "prompt": "/loop 15m check every open PR labeled `codex-watch` and keep each healthy: fix CI failures, rebase when behind main, and nudge if a review is pending",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Label the PRs you want managed, then let this run. Multi-PR loops burn tokens quickly, so scope the label carefully.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "loops!",
        "url": "https://loops.elorm.xyz/loops"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "babysit-a-pr",
      "title": "Babysit a PR",
      "url": "https://looprepo.dev/loops/babysit-a-pr",
      "loopType": "loop",
      "category": "review",
      "difficulty": "beginner",
      "costRisk": "medium",
      "agents": [
        "claude-code"
      ],
      "tags": [
        "pr",
        "review",
        "github"
      ],
      "safety": {
        "grade": "D",
        "score": 45
      },
      "provenance": {
        "tier": "community",
        "label": "0xAndros",
        "authority": 40,
        "githubStars": null
      },
      "description": "Re-run a PR review every 20 minutes so new commits and review comments get handled without you watching the thread.",
      "prompt": "/loop 20m /review-pr 1234",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Swap 1234 for your PR number. Popularized as part of Boris Cherny's Claude Code workflow; stop the loop once the PR merges.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "0xAndros",
        "url": "https://x.com/0xAndros/status/2064063929517777147"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "watch-tests-every-15m",
      "title": "Watch tests while you work",
      "url": "https://looprepo.dev/loops/watch-tests-every-15m",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "beginner",
      "costRisk": "low",
      "agents": [
        "claude-code",
        "codex",
        "cursor"
      ],
      "tags": [
        "tests",
        "watcher",
        "feedback"
      ],
      "safety": {
        "grade": "D",
        "score": 50
      },
      "provenance": {
        "tier": "community",
        "label": "cnemalek",
        "authority": 40,
        "githubStars": null
      },
      "description": "A passive watchdog loop that reruns your test suite every 15 minutes and surfaces failing tests with their error output.",
      "prompt": "/loop 15m run the test suite, and if anything fails, show me the failing tests and the error output",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Great background companion while you edit code by hand. It only reports, never edits, so risk is minimal.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "cnemalek",
        "url": "https://x.com/cnemalek/status/2062977991328583923"
      },
      "published": "2026-07-02"
    },
    {
      "slug": "kill-flaky-tests",
      "title": "Kill flaky tests",
      "url": "https://looprepo.dev/loops/kill-flaky-tests",
      "loopType": "loop",
      "category": "testing",
      "difficulty": "intermediate",
      "costRisk": "high",
      "agents": [
        "claude-code",
        "cursor"
      ],
      "tags": [
        "flaky",
        "tests",
        "stability"
      ],
      "safety": {
        "grade": "C",
        "score": 70
      },
      "provenance": {
        "tier": "community",
        "label": "ericzakariasson",
        "authority": 40,
        "githubStars": null
      },
      "description": "Run your test suite repeatedly, collect every intermittent failure, and fix or quarantine flaky tests until you get five consecutive green runs.",
      "prompt": "/loop run my test suite 20 times, collect every intermittent failure, fix or quarantine the flaky ones, and don't stop until you get 5 consecutive fully-green runs",
      "useWhen": "",
      "verification": "",
      "steps": [],
      "why": "",
      "notes": "Best run on a branch so quarantine decisions can be reviewed. Expect a long session on large suites; the 5-consecutive-green condition is the exit gate.",
      "upvotes": 0,
      "copies": 0,
      "source": {
        "name": "ericzakariasson",
        "url": "https://x.com/ericzakariasson/status/2064122350866682100"
      },
      "published": "2026-07-02"
    }
  ]
}