Conciseness

Nearly every passage documents non-obvious API behavior ("a repeated name silently replaces the earlier entry", "cohort is the Unix timestamp of the period start", partial-bucket labeling rules) rather than concepts Claude already knows. Not 5 because of redundancy — date-range inclusivity is stated twice (in 'Choosing dates and resolution' and again under 'General guidelines' in Interpreting metrics) — and a few passages could be tightened.

Actionability

Guidance is fully executable: exact tool calls with required flags ("Always call this tool with \"realtime\": true\"), copy-paste-ready JSON payloads ("[\"name\": \"store\", \"values\": [\"app_store\"]..."), concrete URL templates with correct and wrong examples, and exact CLI commands ("rc charts options <chart>"). Not 4 because specific worked examples cover the common cases end to end, including error handling on 400 parameter_error.

Workflow Clarity

A clear three-step sequence (schema → data → analyze) with explicit validation and feedback loops: "On such errors, re-read the options schema instead of retrying guesses", "check each batch for rate-limited calls and re-issue only those", and the mandatory numbered checklist in 'Investigating metric shifts' with stop conditions ("Do not skip step 2"). Not 4 because checkpoints and error-recovery loops are explicit throughout, not merely present.

Progressive Disclosure

Sections are well-headed and internally anchored, but the ~140-line 'Chart Dashboard Links' section is tabular URL-format reference material inlined in SKILL.md with no bundle files at all — matching the anchor 'content that should be separate is inline'. Not 4 because a substantial reference block that clearly belongs in a separate file is inlined; not 2 because the file is well structured with clear headers, not a header-less wall of text.

Specificity

Quotes: "querying charts with get-chart-options-schema and get-chart-data, interpreting subscription metrics, or sharing dashboard chart links" — multiple concrete, named actions covering the skill's full scope. Not 4 because coverage is comprehensive for the domain rather than having minor gaps.

Completeness

Explicit 'when' ("Use when the user asks about RevenueCat data, analytics, charts, or KPIs") paired with an explicit 'what' (querying charts via named tools, interpreting subscription metrics, sharing dashboard links). Not 4 because both what and when are stated with concrete trigger phrases, not merely implied.

Trigger Term Quality

Quotes: "RevenueCat data, analytics, charts, or KPIs", "subscription metrics", "dashboard chart links", "forecasts, projections, or run-rates" — good natural keyword coverage. Not 5 because common user phrasings like "MRR", "churn", "conversion", or "revenue" are absent, which are the terms a RevenueCat user would most often say.

Distinctiveness Conflict Risk

Quotes: "RevenueCat data, analytics, charts, or KPIs" plus an explicit boundary "For forecasts, projections, or run-rates, use revenuecat-forecasting" — a clear niche with distinct triggers and even routing guidance away from a sibling skill. Not 4 because the explicit boundary to the forecasting skill leaves minimal overlap risk.