dk-loop-audit
Audit whether an AI agent can autonomously close the loop on problems in a given area — from discovering a symptom to verifying a fix — without human intervention. Evaluates documentation, diagnostic tools, commands, logs, and flows for completeness and actionability. Generates a gap-focused report with ratings. Use this skill whenever someone wants to assess debugging readiness, check if docs are agent-sufficient, audit a workflow for autonomous solvability, evaluate operational tooling coverage, or wants to know 'could an agent fix this on its own?' Triggers on: 'loop audit', 'audit this flo
npx skills add majiayu000/claude-skill-registry --skill dk-loop-audit --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# /dk-loop-audit — Autonomous Loop-Closing Readiness Audit You're auditing whether the tooling, docs, commands, and flows in a given area are sufficient for an AI agent to autonomously solve problems — from first symptom to verified fix — without stopping to ask a human. This is not a documentation quality check. It's an operational readiness assessment. The question isn't "do docs exist?" but "if an agent hit a wall here at 3am, could it get itself unstuck?" ## Target <audit_target> $ARGUMENTS </audit_target> If the target is empty or vague, ask the user: 1. What area or flow should be audited? (e.g., "odin task execution", "taskit API debugging", "reflection quality issues") 2. Is there a specific scenario that prompted this? (a recent failure where an agent got stuck is the best input) If the user provides a doc path, start there but don't stop there — trace outward to the commands, tools, and flows the doc references. ## The Mental Model An AI agent closing the loop on a problem goes through six stages. A gap at any stage breaks the chain: ``` DISCOVER → DIAGNOSE → HYPOTHESIZE → FIX → VERIFY → DOCUMENT ↓ ↓ ↓ ↓ ↓ ↓ "Something "The root "Changing "Apply "Confirm "Record what is w
- Target
- The Mental Model
- Process
- Step 1: Scope the audit
- Step 2: Walk the agent journey
- Step 3: Rate each stage
- Step 4: Identify the critical gaps
- Output
- Create the report
- Report principles
- Print summary
- Edge Cases
What does the dk-loop-audit skill do?
Audit whether an AI agent can autonomously close the loop on problems in a given area — from discovering a symptom to verifying a fix — without human intervention. Evaluates documentation, diagnostic tools, commands, logs, and flows for completeness and actionability. Generates a gap-focused report with ratings. Use this skill whenever someone wants to assess debugging readiness, check if docs are agent-sufficient, audit a workflow for autonomous solvability, evaluate operational tooling coverage, or wants to know 'could an agent fix this on its own?' Triggers on: 'loop audit', 'audit this flo
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill dk-loop-audit --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.