Conciseness

The body is mostly efficient (tables, thresholds, rules with little padding), but at ~340 lines it includes unnecessary explanation Claude already knows: re-derived definitions of demographic parity/equalized odds with formal conditions, and extended verbatim quotations (GDPR Article 22, Kleinberg/Chouldechova excerpts, EEOC Q&A) that could be tightened to short citations. More than 'minor instances of over-explanation', so below the 4 anchor.

Actionability

Concrete and executable throughout: exact bands ('DPD <= 0.05', '0.05 < DPD <= 0.10', 'DPD > 0.10'), a runnable command ('jq '.sensitive_features' model_card.json'), a four-field waiver format, and precisely triggered rules R1-R6. Minor gap: the body never shows how to compute DPD or run a MetricFrame, and that how-to is not in the bundle either, which keeps it below the 5 anchor.

Workflow Clarity

Steps 1-9 are clearly sequenced and Step 9 is an explicit 8-point gate checklist with per-step rule checks, refuse-to-promote conditions, and a validation safeguard ('Gate against the re-derived tier, never the declared one'). This is an assessment skill, so no fix-retry loop is required; the checklist-plus-explicit-checks structure matches the 5 anchor.

Progressive Disclosure

Two well-signaled, one-level-deep references ([references/alibi-explainability.md], [references/worked-example.md]) both exist and contain no nested references. However, the SKILL.md body itself carries substantial detail - metric definitions with formal conditions and extended legal citation prose - that could partly live in reference files, a minor organization gap that keeps it below the 5 anchor.

Specificity

Lists several concrete actions in third person - 'Assigns a low, medium or high tier', 'lists required artifacts', 'returns promote, needs-work or block' - tied to a clear domain. It falls short of the 5 anchor because coverage has gaps (no mention of fairness metric checks, intersectional analysis, or vulnerability scan triage), and it is clearly above the 3 anchor's '1-2 concrete actions'.

Completeness

Explicitly answers both questions: the 'what' ('Assigns a low, medium or high tier, lists required artifacts and returns promote, needs-work or block') and a concrete 'when' ('Use when an ML model release is up for promotion and someone must decide which fairness and explainability evidence is required, or check the evidence against the model's risk tier'). The 'when' is explicit and specific, matching the 5 anchor rather than the 4 anchor where the trigger 'could be more explicit'.

Trigger Term Quality

Natural phrases a user would say include 'ML model release is up for promotion', 'fairness and explainability evidence', and 'risk tier'. Not a 5 because common synonyms such as 'bias check', 'fairness audit', or 'model card review' are absent; well above the 3 anchor since multiple natural trigger terms are present.

Distinctiveness Conflict Risk

A clear niche - promotion-gating of ML model releases on fairness/explainability evidence with named verdicts - that no generic skill would trigger on. Distinct triggers and outputs give minimal conflict risk, matching the 5 anchor.