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.
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.
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each promise with current product behavior and evidence, then label it proven, partly proven, misleading, unsupported, outdated, or missing evidence.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.
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.
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.
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.
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.
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.
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.
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.
Email is the missing tool in your harness. ConnectMyEmail gives Claude Code and Codex a clean MCP into Gmail, iCloud and IMAP — triage, drafts, follow-ups, on a loop.
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.
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.
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.
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.
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.
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.
"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)
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.
/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
Guardrails: Stop when the goal is verifiably met, or stop after 15 iterations, whichever comes first. Keep changes minimal and never touch files outside the task’s scope.
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.
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.
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.
/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
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.
/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
Rewrite the commit messages on your feature branch to conventional-commit format with meaningful bodies before opening the PR, leaving the code untouched.
/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
Email is the missing tool in your harness. ConnectMyEmail gives Claude Code and Codex a clean MCP into Gmail, iCloud and IMAP — triage, drafts, follow-ups, on a loop.
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.
/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
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.
/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
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.
/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
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.
/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
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.
/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
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.
/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
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.
/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
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.
/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
/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
/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
Email is the missing tool in your harness. ConnectMyEmail gives Claude Code and Codex a clean MCP into Gmail, iCloud and IMAP — triage, drafts, follow-ups, on a loop.