Conciseness

The body is operational throughout (commands, tables, gotchas) and does not explain concepts Claude already knows, but it carries real duplication: the Activation Contract restates the frontmatter trigger list, the CLS colon rule appears in both 'Common mistakes' and the query-patterns warning, the env-binding credential note appears twice, 429-vs-AI-429 routing is stated three times, and the 'AIOps Methodology' section is conceptual padding. This is more than minor trimming, so it sits at 'mostly efficient but could be tightened' rather than 4.

Actionability

Guidance is fully executable: exact MCP calls with actions and parameters ('queryEnv(action="metrics", envId="<EnvId>", metricName="GatewayTraceEnvQPS")'), copy-paste CLS query strings per scenario, a complete report template, a patrol state-file schema keyed by 'metricName + scope', and explicit decision rules for when to report a finding. Specific examples cover the common cases across all four inspection modes.

Workflow Clarity

The Full Inspection Workflow is a clearly sequenced 7-step process with explicit validation checkpoints (bind env before anything, checkLogService before log diagnosis, the empty-result three-cause rule before declaring health), plus a minimal checklist and patrol failure handling ('a check ran last time but could not run this time'). The skill is read-only, so the destructive-operation cap does not apply; checkpoints and error-recovery guidance are pervasive, matching the top anchor.

Progressive Disclosure

Both referenced files (references/alarm-interpretation.md, references/fault-playbooks.md) are real, one level deep, and clearly signaled with purpose ('Alarm interpretation baselines ->', 'Fault playbooks ... ->'), and the SKILL.md appropriately keeps overview and core workflows inline. However, the ~30-name PostgreSQL metrics namespace enumeration in the Targeted Inspection section and the long sibling-skill routing list are inlined content that clearly belongs in a reference file, leaving minor organization gaps.

Specificity

The description lists multiple concrete actions with comprehensive coverage: 'health checks, log diagnosis, alarm interpretation (CPU alert normal?, peak QPS), metrics via queryEnv(action=metrics), fault playbooks for 429 / AI model 429 / function timeout / function 404 / ACCESS_TOKEN_INVALID / zero invocations', and 'a scheduled patrol that reports only new or worse findings'. It names the exact tool call and exact error codes rather than generic capability language, matching the comprehensive-coverage anchor rather than the minor-gaps anchor below it.

Completeness

Both 'what' (AIOps-style CloudBase inspection covering checks, diagnosis, alarm interpretation, metrics, playbooks, patrols) and 'when' ('Use when users need...' plus an explicit 'Triggers on...' list) are clearly and explicitly stated with concrete trigger phrases, matching the top anchor. A missing 'Use when' clause would cap this at 3, but it is present and specific.

Trigger Term Quality

Trigger terms cover natural user phrasings in two languages with synonym variants: '巡检, 诊断, 告警, 峰值 QPS, 限频, 调用量为 0, 定时巡检, 每天检查, 值守, troubleshooting' — three distinct phrasings for the scheduled-patrol use case alone. This matches comprehensive natural-term coverage rather than 'a few natural terms missing'.

Distinctiveness Conflict Risk

The CloudBase read-only inspection niche is clear and error-code triggers like ACCESS_TOKEN_INVALID and 调用量为 0 are highly distinctive, but generic terms ('health checks', 'troubleshooting') create minor overlap risk with sibling diagnostic skills in the same plugin. It is mostly distinct with minor overlap rather than minimal conflict risk, so it sits at 4 rather than 5.