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Loop creator

Skill scoobydrew83/skills/plugins/coordinated-skills/skills/loop-creator

A coordinated library of Claude skills with explicit phase/handoff routing, shared state, and a maker/checker loop.

Install
npx -y skills add scoobydrew83/skills --skill loop-creator

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Design and generate autonomous/semi-autonomous AI work loops and the prompts that drive them — builder/verifier (maker/checker) loops, phased build loops, queue-driven multi-task loops, and nightly triage. Every loop it produces has explicit acceptance criteria, a verifier separated from the builder ("close is FAIL"), commit checkpoints, a hard max-iteration + human-escalation stop, and safe stopping conditions. Use whenever the user wants to build a loop, "create a loop", "make a loop creator", set up a self-correcting or maker/checker loop, write prompts for a loop, design an evaluator-optimizer or agentic loop, scaffold a LOOP_QUEUE, or wire a nightly triage workflow — even if they don't say the word "loop" but describe an iterate-until-it-passes process. When (and only when) the request says to look at a codebase or use Claude Code, it inspects the repo read-only and emits a headless Claude Code harness. Defaults to the Conductor Method conventions, all clearly overridable.

SKILL.md

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Loop Creator

Builds work loops — a builder step, a separate verifier step, and a controlled iterate-until-it-passes cycle — plus all the prompts, queue, harness, and CI to run them.

The output is a loop package: a spec, the prompts, a queue, a runnable harness, and (optionally) a GitHub Actions triage workflow. Everything it produces is then run through a bundled validator so the loop can't ship without acceptance criteria, a real verifier, checkpoints, and a stop condition.

Why loops are built this way (the non-negotiables)

These come straight from Anthropic's agent guidance and how the Claude Code team runs loops. They are the spine of every package this skill emits. See references/loop-patterns.md and references/claude-code-loops.md for the grounding.

  1. The doer never grades its own work. A loop is a generator (builder/maker) plus a separate-context evaluator (verifier/checker). The verifier's job is to try to refute success, not rubber-stamp it.
  2. "Close is FAIL." Acceptance criteria are explicit and testable. Partial credit is how loops drift. A verifier that can't cleanly distinguish pass from fail makes the loop circular and useless — so criteria must be concrete (a command that exits 0, a test that passes, a string that appears).
  3. Verify by evidence, not assertion. The builder must show the command it ran and what it returned (test output, lint result, diff). Reviewing evidence is faster and safer than trusting "done."
  4. Checkpoints are commits. Each passed unit of work commits. Small, reviewable, one goal per change. This is the rollback point and the audit trail.
  5. Hard stop + human escalation. Every loop has a max-iteration ceiling and a consecutive-FAIL threshold (default 3). On hitting it, the loop stops and escalates to a human — it never grinds forever and never "decides" to merge anyway.
  6. Never autonomously merge; prefer reversible actions; least privilege. Loops leave work on a branch / open a PR for human approval. Destructive or irreversible steps are gated.
  7. Guard against comprehension debt. Each checkpoint must include a plain-language summary of what changed and why, so a human can actually understand merged code instead of inheriting a black box.
  8. Start simple. Reach for the smallest loop shape that fits. Add stages only when they demonstrably help. Over-engineered planning and monolithic agents are antipatterns.

If the user asks for a loop that violates 1, 2, or 5 (e.g. "no verifier, just let it run forever and merge"), don't silently comply — explain the risk and offer the safe shape. They can still override deliberately, but it should be a choice, not an accident.

Workflow

1. Capture intent

Pin down, from the conversation first and the user second:

  • The goal — what the loop is trying to accomplish, and what "done" looks like.
  • Acceptance criteria — how a single unit of work is judged PASS/FAIL. Push for concrete, runnable checks. Vague criteria are the #1 failure mode; fix them here.
  • Codebase / Claude Code in scope? Default no. Switch to codebase mode only if the request says to look at a repo or use Claude Code.
  • Risk surface — does the loop touch real files, push commits, deploy? This sets how tight the safety gates are.

2. Decision checkpoint (interactive)

Before generating anything, surface the load-bearing choices and confirm them. Don't assume — present them as a short checkpoint. The choices that actually change the output:

  • Loop shape (see references/loop-patterns.md for selection):
    • Builder + verifier — single task, evaluator-optimizer. The default starting point.
    • Phased build loop — multi-phase feature with a gate per phase (Conductor Method).
    • Queue-driven — many tasks from a LOOP_QUEUE.md, one at a time.
    • Nightly triage — scheduled scan that queues work but never fixes autonomously.
  • Execution surface — prompts-only (human drives) vs. headless Claude Code harness.
  • Conventions — Conductor defaults (below) vs. overrides.
  • Escalation threshold and max iterations.

3. Codebase mode (opt-in only)

Only if the request brought a repo into scope. Read before writing:

  • Inventory read-only: glob/grep, README, CLAUDE.md, the build/test/lint commands, package manifests, CI config. Map the real subsystems.
  • Derive acceptance criteria from real commands in that repo (the actual test runner, the actual linter), not invented ones.
  • Then follow references/claude-code-loops.md to wire the headless harness (claude -p), plan mode for exploration, least-privilege tools, and stopping conditions.

4. Generate the loop package

Fill the templates in assets/templates/ with the captured specifics. A full package is:

FilePurpose
LOOP_SPEC.mdGoal, acceptance criteria, loop shape, limits, safety, conventions
builder-prompt.mdThe maker prompt — does work, shows evidence, writes checkpoint summary
verifier-prompt.mdThe checker prompt — fresh context, "close is FAIL", correctness-only
LOOP_QUEUE.mdThe work queue (for queue-driven / triage shapes)
run_loop.shThe harness that drives builder→verifier→commit with limits & escalation
loop-triage.yml(triage only) GitHub Actions that scans and appends to the queue

Apply Conductor defaults from references/conductor-conventions.md, and clearly mark each as overridable in LOOP_SPEC.md so the user can dial it to their context.

For prompts-only output, emit LOOP_SPEC.md + the two prompts (+ queue if relevant) and skip the harness/CI.

5. Self-validate (always)

Run the bundled validator on the generated package and fix anything it flags before handing over:

python3 scripts/validate_loop_package.py <path-to-generated-package>

It checks the non-negotiables: acceptance criteria present and testable; verifier exists and is separate from the builder; "close is FAIL" enforced; checkpoint/commit defined; max-iteration ceiling and escalation threshold present; stopping + safety conditions present; evidence requirement present; comprehension-debt summary required. Show the user the report.

6. Present

Hand over the package (the generated loop files). Point the user at LOOP_SPEC.md first, then how to run run_loop.sh. Keep the wrap-up short.

Conductor defaults (overridable)

Unless told otherwise, loops inherit: builder/verifier role split; LOOP_QUEUE.md as the work queue; "close is FAIL"; commit checkpoint per passed unit; escalate to human after 3 consecutive FAILs; nightly automation is triage-only (queues, never fixes); never auto-merge to the default branch. Full detail and rationale in references/conductor-conventions.md.

References

  • references/loop-patterns.md — loop shapes, when to use each, antipatterns (grounded in Anthropic's "Building Effective Agents").
  • references/claude-code-loops.md — headless claude -p, codebase exploration, GH Actions, the documented safeguards, evidence-based verification.
  • references/conductor-conventions.md — the Conductor Method defaults and why they exist.

Next steps: After the loop package is generated and self-validated, suggest reality-check to pressure-test the acceptance criteria and harness for fabricated commands or unverifiable claims before anyone runs it, and drift-check if this loop joins several specs/prompts that could contradict each other. If the user actually just needed a single Claude Code /goal line rather than a whole package, point them to goal-builder instead. Skip the suggestion if they only wanted a quick scaffold and are done.

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