Conciseness

The workflow, philosophy, and known-limitations sections are tight and earn their tokens, but the ~80-line Anti-Patterns section largely duplicates the dedicated references/anti_patterns.md ('detailed anti-pattern explanations with root causes and correct alternatives'), several entries restate PromQL fundamentals Claude already knows (e.g., 'rate() and increase() need a range vector', 'NEVER average pre-calculated quantiles'), and the 'Validation Tools' section repeats the Step 1-2 script invocations. Mostly efficient with some unnecessary or duplicated material — between the score-2 and score-3 anchors.

Actionability

Guidance is fully executable: copy-paste commands with quoted arguments ('./scripts/validate_syntax.py "<query>"'), five verbatim clarifying questions to ask the user, an explicit citation format ('file_path (lines X-Y)' with a worked example), and concrete limitation examples. This matches the score-5 anchor of copy-paste-ready commands covering the common cases.

Workflow Clarity

The seven steps are clearly sequenced across two phases with script validation in Steps 1-2, an explicit interactive checkpoint ('⏸️ STOP HERE AND WAIT FOR USER RESPONSE before proceeding'), and an intent-vs-implementation comparison with user feedback in Step 5. This matches the score-5 anchor: clear sequence, explicit validation steps, and feedback loops.

Progressive Disclosure

Good structure: clear sections, a References section that signals every bundle file with its purpose, and one-level-deep references that all exist (references/best_practices.md, references/anti_patterns.md, assets/*.promql). It falls between the score-3 and score-4 anchors because the inlined Anti-Patterns section overlaps the dedicated anti-patterns reference (content that could live in the separate file), and the Step 6 citation-format example references 'examples/bad_queries.promql' while the actual path is 'assets/bad_queries.promql'.

Specificity

Lists multiple specific concrete actions — 'validating, optimizing, and understanding' PromQL queries plus 'check syntax, detect anti-patterns, identify optimization opportunities, and interactively plan queries' — giving comprehensive coverage of the skill's capabilities. It exceeds the score-4 anchor ('several specific actions; minor gaps') because the action list spans the full validate-explain-optimize workflow with no obvious gaps.

Completeness

Explicitly answers both questions: 'what' (validate, optimize, and understand PromQL queries; check syntax, detect anti-patterns, identify optimizations) and 'when' ('Use this skill when working with PromQL queries... grafana dashboards') with concrete trigger phrases. This matches the score-5 anchor exactly.

Trigger Term Quality

Natural trigger terms are comprehensively covered with synonyms and variations: 'PromQL queries, prometheus queries, metrics queries, alerting rules, recording rules, grafana dashboards'. These are the phrases a user would naturally say; no common variation is missing.

Distinctiveness Conflict Risk

The PromQL-validation niche is clear and distinct, but broad trigger terms like 'prometheus queries' and 'grafana dashboards' create minor overlap risk with closely related skills (e.g., a promql-generator or dashboard-authoring skill). It sits between the score-4 ('mostly distinct; minor overlap risk with closely related skills') and score-5 anchors, and the shared 'prometheus/grafana' vocabulary with adjacent skills keeps it at 4.