Conciseness

The body is dense and imperative throughout — 'Classify the request once, create the smallest useful handoff envelope, then pass that envelope forward' — with no explanation of concepts Claude already knows. Minor trim opportunities keep it from 5: the ten-item envelope field list, and editing-pass budget rules repeated across 'Multi-stage sequencing', 'Boundary changes', and 'Stop conditions'.

Actionability

Concrete, executable routing rules: 'Scan, detect, audit, score, or flag-only requests go to `ai-writing-detector`', a numbered seven-stage sequence, typed-edge semantics, an explicit 'Do not' checklist, and concrete output requirements ('include exactly one full Final rewrite', 'report changed spans without dumping a duplicate of the file'). Not 5 because no worked example of a filled handoff envelope is given, sub-skill paths are bare identifiers, and the actual pass-cap number is deferred to the canonical skill.

Workflow Clarity

The multi-stage flow is a numbered sequence with an explicit validation gate ('preservation-verifier checks before/after material'), a bounded repair feedback loop ('A verifier FAIL returns to the correct repair owner once only if the shared budget has room'), re-verification after repair, an explicitly bounded residual check, and clear stop conditions — matching the anchor for clear sequence with explicit validation steps, error-recovery feedback loops, and checklists.

Progressive Disclosure

The body is a genuine overview: all four references/ files exist and each is named with its purpose ('references/skill-graph.json is the machine-readable source for nodes, typed edges, guards, and loop limits'), and references are one level deep, cross-linking only as siblings. The gap that keeps it from 5 is that scripts/validate_connections.py — a real bundle file validating the graph — is never mentioned in SKILL.md or in any reference file, making it undiscoverable despite 'Review lenses' mentioning 'CI and drift checks'.

Specificity

The description enumerates several concrete action areas — 'AI-writing audit, rewrite, file editing, voice preservation, false-positive interpretation, verification' — matching the 'several specific actions with minor gaps' anchor. It falls short of 5 because the skill's own function (routing/coordination) is never named, and above 3 because it lists far more than 1-2 concrete actions.

Completeness

The 'when' is explicit and detailed ('Use when a request combines... or when the user invokes Avoid AI Writing without naming a mode'), but no statement of what the skill does (coordinate a bounded routing workflow) appears — it is only weakly implied by the enumerated task types. This sits between the 'only when present without what' anchor (2) and the clear-half anchor (3), above the midpoint because the when-clause is unusually rich.

Trigger Term Quality

Relevant keywords exist ('audit', 'rewrite', 'file editing', 'verification', 'Avoid AI Writing') but the colloquial phrases users would actually say — 'make this sound less AI', 'humanize', 'reads as AI-generated' — are absent, and 'voice preservation' and 'false-positive interpretation' are internal jargon. This matches 'some relevant keywords but missing common variations or synonyms' rather than anchor 4's 'good keyword coverage'.

Distinctiveness Conflict Risk

Niche-specific vocabulary ('voice preservation', 'false-positive interpretation', 'Avoid AI Writing') plus a named-invocation trigger gives a clear niche with minimal conflict risk, matching 'mostly distinct; minor overlap risk'. Not 5 because the bare terms 'rewrite' and 'file editing' could overlap generic editing skills, bounded only by the 'combines' qualifier.