grtninja/skill-auditor

Skill Auditor

Use this skill to classify and gate new or updated skills.

Workflow

1. Select changed skills (--include-skill) or scan the full candidate set.
2. Run the skill audit script to classify each skill as unique or upgrade.
3. Validate core quality checks:
   • frontmatter completeness (name, description),
   • agents/openai.yaml presence,
   • size/readability guardrails,
   • required arbiter evidence when enabled,
   • meta-harness drift such as legacy Documents\GitHub roots or :1234 treated as an authority surface.
4. Review findings by severity (high, medium, low) and fix failures.
5. Re-run until high_count=0 for admission-ready output.

Commands

Audit selected skills:

python3 scripts/skill_audit.py \
  --skills-root skill-candidates \
  --include-skill <skill-name> \
  --json-out /tmp/skill-audit.json

Audit with arbiter evidence required:

python3 scripts/skill_audit.py \
  --skills-root skill-candidates \
  --include-skill <skill-name> \
  --arbiter-report /tmp/skill-arbiter-evidence.json \
  --require-arbiter-evidence \
  --json-out /tmp/skill-audit.json

Classification Rules

• unique: no strong near-peer overlap detected in current skill set.
• upgrade: near-peer overlap indicates refinement/extension of an existing lane.
• high findings block completion.
• medium findings should be addressed before admission when possible.
• Meta-harness-sensitive skills should also encode the canonical G:\GitHub root contract, authoritative :9000/:2337 model lanes, and PC Control-first evidence rules where applicable.

Scope Boundary

Use this skill only for skill-audit classification and findings generation.

Do not use this skill for runtime skill arbitration; use $skill-arbiter-lockdown-admission.

References

• references/audit-rubric.md
• scripts/skill_audit.py

Loopback

If findings remain unresolved:

1. Capture failing checks and evidence paths.
2. Route through $skill-hub for chain recalculation.
3. Resume only after an updated chain assigns deterministic fixes.