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ops-inspector

AIOps-style CloudBase inspection skill (v3). Use when users need health checks, log diagnosis, alarm interpretation (CPU alert normal?, peak QPS), metrics via queryEnv(action=metrics), or fault playbooks for 429 / function 404 / ACCESS_TOKEN_INVALID / zero invocations. Triggers on 巡检, 诊断, 告警, 峰值 QPS, 限频, 调用量为 0, troubleshooting.

73

Quality

91%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is ops-inspector in TencentCloudBase/CloudBase-AI-Toolkit

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a highly actionable, well-sequenced diagnostic playbook with real reference files for deeper detail. Its main weakness is moderate verbosity in the methodology/restatement sections and implied rather than explicit feedback loops between metrics and playbooks.

Suggestions

Trim or fold the 'AIOps Methodology' section into the workflows — its five principles are already demonstrated by the steps, and consolidate the repeated 'Never use callCloudApi for metrics' into a single callout to save tokens.

Make the metrics→playbook feedback loops explicit in the Full Inspection Workflow (e.g. after Step 2, add 'If Summary.allZero or FunctionThrottle non-zero → jump to the matching fault playbook') so recovery paths are checkpoints, not implications.

Consider moving the Common CLS Query Patterns and Time Range Guidance tables into a reference file to shorten SKILL.md and keep it as a true overview, since they are lookup material rather than core workflow.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete tool calls, tables, and checklists, but the 'AIOps Methodology' section restates what the workflows already show and the 'Never use callCloudApi' prohibition is repeated several times, giving minor over-explanation that could be trimmed.

4 / 5

Actionability

Fully executable guidance throughout — exact tool calls like queryEnv(action="metrics", envId, metricName="GatewayTraceEnvQPS"), ready-to-use CLS queryString patterns, named metrics, console links, and a copy-paste report template covering common cases.

5 / 5

Workflow Clarity

A clear 7-step inspection sequence with explicit checkpoints (env-bound check, CLS-enable warning, time-range gating) and a minimal checklist; read-only diagnostics avoid the destructive-cap, but a few feedback loops (e.g. metrics allZero → playbook) are implied rather than explicit.

4 / 5

Progressive Disclosure

Good structure with one-level-deep references to real bundle files (references/alarm-interpretation.md, references/fault-playbooks.md) and sibling skills, clearly signaled via the 'Then also read' section; baselines and playbooks are appropriately split out, though the body itself remains fairly long with inlined tables.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: it states concrete capabilities, gives explicit bilingual trigger guidance covering both 'what' and 'when', and occupies a clear niche with low conflict risk. It does not pad or over-claim.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'health checks, log diagnosis, alarm interpretation (CPU alert normal?, peak QPS), metrics via queryEnv(action=metrics), or fault playbooks for 429 / function 404 / ACCESS_TOKEN_INVALID / zero invocations' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both 'what' (CloudBase inspection, alarm interpretation, fault playbooks) and 'when' with concrete 'Use when...' and 'Triggers on...' clauses, matching the 5-anchor.

5 / 5

Trigger Term Quality

Covers natural bilingual trigger phrases users would actually say — '巡检, 诊断, 告警, 峰值 QPS, 限频, 调用量为 0, troubleshooting' — plus concrete error codes, giving comprehensive synonym/variant coverage.

5 / 5

Distinctiveness Conflict Risk

The 'AIOps-style CloudBase inspection' niche plus specific error codes (429, function 404, ACCESS_TOKEN_INVALID) and the dedicated metrics tool make it clearly distinct with minimal conflict risk.

5 / 5

Total

20

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
TencentCloudBase/CloudBase-AI-Toolkit
Reviewed

Table of Contents

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