Conciseness

The operational core (dispatch, steps, output contract) is lean, but the body carries noticeable non-instructional material: the model-pin history parenthetical ('it no longer pins one — a hard model pin capped the usable context…'), provider-specific Haiku versioning repeated twice (intro and 'Why this is a separate skill'), and time-sensitive version numbers ('Haiku 5.5', '1M window', '200k window') outside any deprecated section. Mostly efficient but could be tightened — matching the 3 anchor; the duplication is more than the 'minor instances' of 4, while the lean operational core keeps it above 2.

Actionability

Fully executable guidance throughout: the exact helper command ('python3 scripts/audit-extract.py $ARGUMENTS[1] --mode $ARGUMENTS[0]'), literal-equality dispatch table, exact accepted file patterns, a verbatim usage message to print, exact sidecar/markdown output paths with field sources, a precise write order, and an explicit tool directive ('Use the Write tool directly… Do NOT generate a Python script'). Copy-paste ready and covers the common cases.

Workflow Clarity

Clear 5-step sequence with explicit validation checkpoints: missing/invalid path argument triggers a verbatim usage message and stop, digest.scope drives reference routing, and config files are capped at ≤500 lines with the violation itself flagged as a finding. It falls short of 5 because there is no error-recovery guidance for helper failure or a malformed digest — no feedback loop — leaving minor validation gaps at the 4 anchor.

Progressive Disclosure

SKILL.md is a genuine overview: routing tables specify exactly which of the five reference playbooks to read per scope/mode, and all five referenced files (quick-audit.md, detailed-audit.md, project-quick-audit.md, project-detailed-audit.md, instance-quick-audit.md) exist in references/ with a when-to-read description each. References are one level deep — playbooks defer to the shipped script, not to further documents — matching the 5 anchor.

Specificity

Lists multiple concrete actions — 'Audit a session-metrics JSON export for token-usage waste and produce a plain-English findings report' with mode-specific sub-actions ('ratios + cache health + top expensive turns/sessions', 'adds CLAUDE.md / settings / re-read scan') and three named JSON scopes — giving comprehensive, specific coverage.

Completeness

Explicitly answers both 'what' (audits a session-metrics JSON export for token-usage waste, produces a plain-English findings report) and 'when' with concrete trigger phrases ('Trigger when the user runs /audit-session-metrics, when session-metrics suggests an audit after an HTML export, or when the user asks to audit / review / find waste in a saved session-metrics JSON'). This matches the 5 anchor exactly; the 'when' clause is fully explicit, not merely present.

Trigger Term Quality

Includes natural trigger phrases users would say ('audit / review / find waste in a saved session-metrics JSON', '/audit-session-metrics', 'after an HTML export'), but omits common synonyms like token usage, cost, or spending that a user might naturally use. Good coverage with a few natural terms missing, matching the 4 anchor rather than the comprehensive synonym coverage of 5.

Distinctiveness Conflict Risk

Clear niche tied to a specific artifact — session-metrics JSON exports — with distinct triggers; even the generic verbs ('audit / review / find waste') are scoped to that artifact, so overlap risk with other skills is minimal.