Conciseness

Dense with internal facts Claude cannot know (metric names, tolerances, log field schemas, query_id patterns) with essentially no generic explanation, but with minor trim opportunities: tolerances are stated twice within one section ('Funnels strict (`0.1%`)' then 'STRICT_TOLERANCE = 0.001'; 'loose `2%`' then 'LOOSE_TOLERANCE = 0.02'), and incident-history asides carry time-sensitive detail inline ('Since PR #87880 (2026-08-25)'). Fits the 4 anchor (efficient, minor instances that could be trimmed) rather than 5 (every token earns its place).

Actionability

Fully concrete for an MCP-driven investigation: exact metric names ('experiment_precompute_canary_outcomes'), an exact PromQL fragment ('time() - experiment_precompute_canary_last_run_timestamp'), exact log event names with full field lists, exact thresholds ('MIN_CORRECTNESS_SUM_DELTA = 100'), a copy-paste report template, and per-scenario next actions. The absence of hardcoded MCP tool/label names is explicitly justified flexibility ('First discover the exact Prometheus query tool the MCP exposes', 'Discover the Loki label schema... don't hardcode labels'), so the rubric's pseudocode penalty does not apply.

Workflow Clarity

Clear sequence (health sweep → conditional deep dive → classification → report) gated by explicit per-region verdict criteria (Healthy/Stale/Unhealthy), with real feedback loops: 'If outcomes shows divergence but no matching log line is found, widen the time range; if still nothing, say so — don't invent', 'check the Temporal schedule... exists and isn't paused', and drift handling ('trust the code and note the drift in your report'). The classification taxonomy in step 3 is a complete checklist; the operation is explicitly read-only, so no destructive/batch validation cap applies.

Progressive Disclosure

Well-organized single-file structure with clear section headers, and its source-of-truth pointers ('products/experiments/backend/temporal/canary_logic.py', 'tools/infra-scripts/mcp/README.md') are clearly signaled (both outside the skill bundle; no references/ directory exists). At ~190 lines, the Background section's incident history and tolerance rationale are inlined context that could live in a short reference file. Fits the 4 anchor (good structure, minor organization gaps) rather than 5, which expects an overview with well-signaled one-level-deep references.

Specificity

Lists multiple concrete actions — 'Sweeps the canary's Prometheus health gauges in both regions', 'pulls the structured divergence/failure logs from Loki to reconstruct exactly which (team, experiment, metric) went wrong, by how much, and which class of divergence it is' — plus an explicit scope boundary ('Mechanism-level root cause needs ClickHouse and is out of scope — the skill hands off with precise drill-down steps'), all in third-person voice. Matches the 5 anchor (multiple specific concrete actions, comprehensive coverage); not 4, because coverage of the skill's behavior is complete with no real gaps.

Completeness

Explicitly answers both: what ('Analyze the experiment precompute result-consistency canary across prod-US and prod-EU, deep-dive any issues, and produce an actionable report') and when (a literal 'Use when...' clause with concrete trigger phrases). Matches the 5 anchor exactly; not 4, because the 'when' is fully explicit with multiple concrete triggers rather than merely present.

Trigger Term Quality

'Use when the user asks to check / analyze / verify the experiment precompute canary, investigate a canary divergence or alert, or confirm precomputed experiment results are consistent in production' gives five natural verb triggers plus the key nouns (canary, divergence, alert, experiment results, production). A few everyday phrasings a user might naturally say ('canary failing/unhealthy', 'results don't match') are absent, which fits the 4 anchor ('good keyword coverage; a few natural terms missing') better than 5's comprehensive synonym coverage.

Distinctiveness Conflict Risk

Clear niche — 'experiment precompute result-consistency canary', 'prod-US and prod-EU', 'Grafana MCP (Prometheus + Loki)' — where every trigger phrase names the canary, a canary divergence/alert, or precomputed experiment results. Virtually no overlap risk with generic monitoring or data-analysis skills; matches the 5 anchor ('clear niche with distinct triggers; minimal conflict risk').