Which AI agents does this loop work with?

Draft a sprint plan from the backlog is written for claude-code, codex.

Is this loop safe to run unattended?

This loop is graded B (80/100) by looprepo's automatic safety evaluator, which checks for exit conditions, iteration budgets, verification steps, and scoping before publishing.

/goal planninglow riskintermediatesafety B · 80 looprepo

Draft a sprint plan from the backlog

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

→ Claude

/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

⧉ 1 copiesclaude-code · codex

Implementation note

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.

Source: looprepo ↗

More planning loops

loop-init, loop-audit, loop-cost CLI patterns

/ralphnew

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

→ Claude

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.

planningmedium risk

Ralph the PRD backlog

/ralphGeoffrey Huntleynew

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

→ Claude

/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

planninghigh risk

Set agent continuation budget

/goalnew

Configure max turns before agent stops, preventing runaway loops and controlling execution cost.

prompt

→ Claude

/goal budget <n Set max continuation turns

planninglow risk

source ↗