Conciseness

Mostly efficient but redundant in places — the T1–T4 and M1–M4 veto dimensions are restated in Step 1/Step 6 summaries and again in the final report template, and the changelog reiterates rationale at length. It is tight enough to stay above a 2 but not lean enough for a 4.

Actionability

Provides concrete commands ('python scripts/evaluate_skill.py'), copy-paste report templates, exact JSON key names, and a strict pre-emit checklist; minor gaps (e.g., the script's CLI args are not enumerated inline) keep it just short of fully copy-paste ready.

Workflow Clarity

The 8-step pipeline is clearly sequenced with explicit hard gates at Steps 1 and 6, validation feedback loops ('fix all FAIL dimensions before resubmitting'), fallback paths, and a destructive-overwrite pre-emit checklist — matching the validate→fix→retry anchor.

Progressive Disclosure

The body is an overview pointing to 11 one-level-deep reference files, all of which exist on disk and are clearly signaled via a reference table with 'Used In' and 'Gate?' columns, giving clean navigation.

Specificity

Lists multiple concrete actions — 'two hard veto gates', 'static quality scoring across 25 criteria', 'dynamic test input generation', 'five specialized category rubrics', 'P0/P1/P2 optimization recommendations' — with comprehensive coverage.

Completeness

Explicitly answers both what it does and when to use it via 'Use this skill whenever a user wants to evaluate, audit, review, score, or quality-check an agent skill' plus concrete trigger phrases.

Trigger Term Quality

Includes natural user phrasings ('evaluate, audit, review, score, or quality-check') plus literal triggers like 'audit my skill', 'evaluate my skill', 'improve my skill' that users would actually say.

Distinctiveness Conflict Risk

Occupies a clear niche (auditing agent skills before publishing/deploying) with distinct triggers, so overlap with other skills is minimal.