skill-audit

Scans all skill locations (global, workspace, project) and produces a structured audit report.

What It Checks

Structural Quality (per skill)

1. Description quality — Is the description field trigger-oriented (tells the model when to use it) vs a vague summary?
2. Gotchas section — Does the SKILL.md include a Gotchas/Pitfalls/Common Issues section? (Highest-signal content per Anthropic)
3. Progressive disclosure — Does the skill use subdirectories (scripts/, references/, assets/, examples/) or is it a flat SKILL.md?
4. File structure — Are there scripts, templates, or reference files the agent can discover?
5. YAML frontmatter — Does it have name, description, and optionally compatibility?
6. Category fit — Does it map cleanly to one of the 9 skill categories (Library/API, Verification, Data, Automation, Scaffolding, Code Quality, CI/CD, Runbooks, Infrastructure)?

Cross-Skill Issues

7. Duplicates — Same skill name or overlapping functionality across global/workspace/project dirs
8. Orphan files — Stale .skill files, empty dirs, leftover copies
9. Category gaps — Which of the 9 categories have no skills at all?
10. Stale skills — Skills that reference missing tools, dead paths, or deprecated APIs

How to Run

Tell the agent: "audit my skills" or "run skill-audit"

The agent will:

1. Run scripts/audit.sh to scan all skill locations and collect metadata
2. Score each skill (0-10) based on the checks above
3. Produce a summary report with:
   • Per-skill scorecard
   • Top issues to fix (sorted by impact)
   • Category coverage map
   • Duplicate/orphan findings

Output

Results are written to .sub-agent-results/skill-audit-report.md and summarized in chat.

Scoring

Scores: 8-10 = Good, 5-7 = Needs work, 0-4 = Poor

References

• Anthropic: Lessons from Building Claude Code Skills — Thariq's 9 categories, gotchas sections, progressive disclosure
• Ole Lehmann: Auto-improve Skills — Autoresearch loop (future enhance mode)