Loop Design Checklist

Score a loop design before enabling it for unattended runs. A loop missing key safety controls is not production-ready — this skill helps you find what's missing before it causes problems.

Usage

/loop-design "<loop name or description>"   # score a loop you're about to enable
/loop-design --pattern <name>               # check a named pattern (pr-babysitter, ci-sweep, etc.)
/loop-design --audit                        # audit all currently configured loops

Behavior

Step 1 — Establish the loop under review

If $ARGUMENTS names a pattern (pr-babysitter, ci-sweep, dep-sweep, issue-triage, post-merge, daily-triage), load its known structure. Otherwise, ask:

1. What does this loop do? (one sentence)
2. What is the cadence? (every N minutes/hours/days)
3. What actions can it take? (report-only / propose fix / apply fix / open PR / merge)
4. What external systems does it touch? (GitHub, Linear, Slack, database, etc.)

Step 2 — Score against the readiness checklist

Work through each section and mark PASS / FAIL / MISSING:

Purpose & Scope

• Single clear goal (one sentence)
• Explicit non-goals documented
• Target scope defined (which repos, branches, labels, or queues)
• Phase rollout planned (report-only first, then act)

Scheduling

• Cadence chosen and justified (urgency matches interval)
• Off-hours behavior defined (pause, slow down, or continue)
• Self-cleanup on empty watchlist (no pointless runs)

Maker / Checker Split

• Implementer and verifier are separate agents or models
• Implementer cannot mark its own work "done"
• Verifier runs tests independently before approving
• If no verifier: loop is report-only or escalates all actions to human

State / Memory

• State file or board schema defined
• Loop reads prior state at start of every run
• Loop writes outcomes and timestamps at end of every run
• Resolved/closed items are pruned on each run
• Human overrides are recorded in state

Human Escalation

• Attempt cap defined (e.g. max 3 fix attempts per issue)
• Escalation triggers explicit (cap exhausted, high-risk path, ambiguity)
• Denylist paths configured (auth, payments, secrets, infra)
• Notification channel defined (where does escalation land?)

Cost & Safety

• Token budget estimated per run
• Daily cap defined in loop-budget.md or equivalent
• Kill switch documented (label, flag, or loop-pause-all)
• Run log configured (loop-run-log.md or equivalent)

Connectors (if any)

• Minimum permissions for each connector (read vs write)
• Bot identity clear on any auto-posted comments/PRs
• Write-scope connectors require verifier or human gate

Step 3 — Calculate readiness score

Readiness levels:

• L1 (≥ 60): Safe for report-only runs
• L2 (≥ 80): Safe for supervised fix-proposal runs
• L3 (≥ 95): Safe for unattended fix-apply runs

Step 4 — Surface critical blockers

Flag any FAIL in these items as blockers regardless of score:

• No kill switch → loop can run indefinitely, no way to stop quickly
• No attempt cap → infinite fix loops and token burn possible
• Same agent implements and verifies → confirmation bias, weak tests get approved
• Denylist not configured → loop may touch auth/payments/secrets
• No state file → loop acts on stale or ghost items from prior runs

Step 5 — Output report

LOOP DESIGN REVIEW — PR Babysitter

Readiness Score: 78/100 → L2 (supervised fix-proposal)

PASS (15/20 items)

BLOCKERS (fix before enabling)
  ✗ No attempt cap — CI fix loop could run forever on a hard regression
    Fix: set max_attempts = 3 per PR in state file

GAPS (improve before L3)
  ✗ No run log — token spend is invisible
    Fix: append JSON entry to loop-run-log.md after each sweep
  ✗ Verifier not configured — fixes are self-approved
    Fix: invoke /loop-verify after each /minimal-fix attempt

RECOMMENDATIONS
  → Start in report-only mode (--dry-run) for 3 days
  → Review STATE.md after first week; prune ghost items
  → Add loop-budget.md with daily cap before enabling L2 actions

Suggested first command:
  /loop 10m /pr-babysitter --dry-run

Anti-Patterns Flagged

The checklist specifically surfaces these known failure modes:

Edge Cases

• Pattern name not recognized: Ask for the loop description and score from scratch.
• Existing loop audit (--audit): Find all configured loops by scanning LOOP.md, .github/workflows/, and session schedules, then score each.
• Score exactly at a tier boundary: Recommend the lower tier until blockers are resolved.

Token Optimization

Expected range: 300–800 tokens

Patterns used: Progressive disclosure (score first, blockers second, full checklist on request), early exit (if loop is report-only with no actions, many safety checks are N/A)

No caching needed: Each loop design is unique; scores are not reusable across sessions.