ops-inspector

Sibling skills (local only)

Sibling CloudBase skills ship beside this skill. Use local relative paths such as ../auth-tool-cloudbase/SKILL.md.

If a referenced sibling skill file is missing from this environment, ask the user to install the full CloudBase plugin (or the missing skill). Do not HTTP-fetch remote skill or protocol markdown into the agent context.

Activation Contract

Use this first when

• The user wants to check the health or status of CloudBase resources (cloud functions, CloudRun, databases, storage, etc.).
• The user reports errors, failures, or abnormal behavior and wants a quick diagnosis.
• The user asks for an "inspection", "health check", "巡检", "诊断", or "troubleshooting" of their CloudBase environment.
• The user wants to review recent error logs across services.
• The user asks 告警解读 questions: whether a CPU 告警 is normal, what 峰值 QPS was, or whether throttle/error metrics look healthy.
• The symptom matches a v3 fault playbook: 429 / 限频, 云函数 404, ACCESS_TOKEN_INVALID, or 调用量为 0.

Read before writing code if

• The inspection reveals code-level issues in cloud functions or CloudRun services — then read the relevant implementation skill before suggesting fixes.
• The user wants to fix a problem found during inspection rather than just diagnose it.

Then also read

• Alarm interpretation baselines -> references/alarm-interpretation.md
• Fault playbooks (429 / 404 / token / zero calls) -> references/fault-playbooks.md
• Cloud function issues -> ../cloud-functions/SKILL.md
• CloudRun issues -> ../cloudrun-development/SKILL.md
• Database issues -> ../postgresql-development-cloudbase/SKILL.md for CloudBase PG / PostgreSQL, ../relational-database-mcp-cloudbase/SKILL.md for MySQL, or ../cloudbase-document-database-web-sdk/SKILL.md for NoSQL
• Auth readiness (token failures) -> ../auth-tool-cloudbase/SKILL.md
• Platform overview -> ../cloudbase-platform/SKILL.md

Do NOT use for

• Deploying new resources or writing application code. This skill is read-only and diagnostic.
• Replacing proper monitoring/alerting infrastructure. It provides point-in-time inspection, not continuous monitoring.
• Directly fixing problems — it diagnoses and recommends; actual fixes should use the appropriate implementation skill.
• Fetching metrics by guessing cloud API Actions. Never use callCloudApi for monitor curves — always use queryEnv(action="metrics").

Common mistakes / gotchas

• Running a full inspection without first confirming the environment is bound (auth tool must show logged-in and env-bound state).
• Ignoring CLS log service status — if CLS is not enabled, queryLogs will fail; always check first with queryLogs(action="checkLogService").
• Searching logs without a time range — this can return excessive or irrelevant results. Always scope searches to a relevant time window.
• Treating a single error log as the root cause without correlating across resources. A function error may stem from a database or config issue.
• Answering "峰值 QPS" / "CPU 告警是否正常" from screenshots or memory instead of queryEnv(action="metrics").
• Calling callCloudApi with invented GetMonitorData / DescribeCurveData parameters — the metrics branch already wraps Manager SDK.

Minimal checklist

• Environment is bound and accessible (queryEnv(action="info"))
• Metrics pulled with queryEnv(action="metrics") when the question involves QPS / CPU / throttle / invocation volume
• CLS log service is enabled (queryLogs(action="checkLogService")) when log diagnosis is needed
• Matching fault playbook selected when symptoms match 429 / function 404 / ACCESS_TOKEN_INVALID / 调用量为 0
• Time range is specified for any log or metrics searches
• Findings are summarized with severity levels, 告警解读, and actionable recommendations

How to use this skill (for a coding agent)

Ops Inspector v3 additions

v3 adds two mandatory capabilities on top of log/resource inspection:

1. 告警解读 — pull metrics, compare to baselines in references/alarm-interpretation.md, answer CPU-alert / peak-QPS style questions in plain language.
2. 故障剧本 — when symptoms match, follow references/fault-playbooks.md instead of ad-hoc tool fishing.

Inspection Modes

Full Inspection Workflow

Follow these steps in order for a comprehensive environment health check:

Step 1 — Environment Check

queryEnv(action="info")

Confirm the environment is accessible. Record the envId for console link generation.

Step 2 — Metrics snapshot (v3)

queryEnv(action="metrics", envId="<EnvId>", metricName="GatewayTraceEnvQPS")
queryEnv(action="metrics", envId="<EnvId>", metricName="FunctionInvocation")
queryEnv(action="metrics", envId="<EnvId>", metricName="MysqlCpuUsageRate")

Use returned Summary.max / avg / allZero / peakTimestamp. Add FunctionError, FunctionThrottle, or CloudRun Tke* metrics when those resources exist. Read references/alarm-interpretation.md before concluding.

Step 3 — Log Service Status

queryLogs(action="checkLogService")

If CLS is not enabled, note this as a warning — log-based diagnosis will be unavailable. Recommend enabling CLS in the console: https://tcb.cloud.tencent.com/dev?envId=${envId}#/devops/log

Step 4 — Cloud Functions Inspection

queryFunctions(action="listFunctions")

For each function, check:

• Status: Is the function in an active/deployed state?
• Recent errors: queryFunctions(action="listFunctionLogs", functionName="<name>", startTime="<recent>")
• Common issues:
  • Timeout errors (execution exceeded limit)
  • Memory limit exceeded
  • Runtime errors (unhandled exceptions)
  • Cold start frequency
  • Zero invocations while traffic is expected → Playbook 4

Step 5 — CloudRun Services Inspection

queryCloudRun(action="list")

For each service, check:

• Status: Is the service running?
• Detail: queryCloudRun(action="detail", detailServerName="<name>")
• Metrics: queryEnv(action="metrics", metricName="TkeQPSService", resourceID="<serviceName>") (resourceID required)
• Common issues:
  • Service not running (scaled to zero or crashed)
  • Image pull failures
  • OOMKilled events
  • Health check failures

Step 6 — Error Log Aggregation (if CLS is enabled)

queryLogs(action="searchLogs", queryString="ERROR", service="tcb", startTime="<24h-ago>", limit=50)
queryLogs(action="searchLogs", queryString="ERROR", service="tcbr", startTime="<24h-ago>", limit=50)

Look for patterns:

• Repeated error messages (same error many times)
• Cascading failures (errors in multiple services around the same time)
• Timeout / 429 / 404 / ACCESS_TOKEN_INVALID patterns → jump to the matching playbook

Step 7 — Summary Report

Generate a structured report:

# CloudBase Resource Inspection Report

**Environment**: ${envId}
**Inspection Time**: ${timestamp}

## Overall Health: ✅ Healthy / ⚠️ Warnings Found / ❌ Issues Found

## 告警解读
| 问题 | 指标 | 窗口峰值 | 基线 | 结论 |
|------|------|----------|------|------|
| 峰值 QPS | GatewayTraceEnvQPS | ... | package default 500 unless known | ... |
| CPU 告警是否正常 | MysqlCpuUsageRate | ... | warn≥80 / crit≥90 | ... |

### Cloud Functions
| Function | Status | Recent Errors | Invocations | Severity |
|----------|--------|---------------|-------------|----------|
| ... | ... | ... | ... | ... |

### CloudRun Services
| Service | Status | Issues | Severity |
|---------|--------|--------|----------|
| ... | ... | ... | ... |

### Error Log Summary
- Total errors in last 24h: N
- Top error patterns: ...

## Recommendations
1. ...
2. ...

## Console Links
- Cloud Functions: https://tcb.cloud.tencent.com/dev?envId=${envId}#/scf
- CloudRun: https://tcb.cloud.tencent.com/dev?envId=${envId}#/platform-run
- Logs: https://tcb.cloud.tencent.com/dev?envId=${envId}#/devops/log
- Monitor: https://tcb.cloud.tencent.com/dev?envId=${envId}#/devops

Targeted Inspection Workflow

When the user specifies a resource type or a specific resource:

1. Cloud function errors: queryFunctions(action="listFunctionLogs", functionName="<name>") then queryLogs(action="searchLogs", queryString="* AND functionName:<name> AND level:ERROR", ...)
2. CloudRun errors: queryCloudRun(action="detail", detailServerName="<name>") then queryLogs(action="searchLogs", queryString="ERROR", service="tcbr", ...)
   • If logs show DB / Redis connection failures (ECONNREFUSED, timeout, "could not connect"): check whether VpcConf is set and matches the database VPC. See cloudrun-development/references/vpc-and-database.md.
3. Database issues: Check queryPgDatabase(action="context"|"metadata"|"objects") for CloudBase PG, queryMysqlDatabase for MySQL, or readNoSqlDatabaseStructure for NoSQL depending on type; for CPU/disk alerts also pull MysqlCpuUsageRate / MysqlStorageUsage metrics
4. General error search: queryLogs(action="searchLogs", queryString="<error-keyword>", ...)
5. Alarm / QPS questions: follow references/alarm-interpretation.md
6. 429 / function 404 / ACCESS_TOKEN_INVALID / 调用量为 0: follow references/fault-playbooks.md

AIOps Methodology

This skill follows AIOps principles for intelligent inspection:

1. Data Collection: Gather metrics (queryEnv metrics), logs, and resource states via MCP tools — never via ad-hoc callCloudApi
2. Pattern Recognition: Identify recurring errors, anomaly patterns, and correlations across services
3. Baseline Comparison: Compare metric Summary values to skill baselines (告警解读)
4. Root Cause Hypothesis: Based on error patterns + metrics, suggest likely root causes
5. Actionable Recommendations: Provide specific, prioritized remediation steps with links to relevant skills and console pages

Severity Levels

Preferred Tool Map

Common CLS Query Patterns

Time Range Guidance

• Quick check: Last 1 hour (startTime = 1 hour ago)
• Standard inspection: Last 24 hours
• Trend analysis: Last 7 days
• Specific incident: Narrow to the reported time window

Always use ISO-like YYYY-MM-DD HH:mm:ss for metrics startTime/endTime, e.g., "2026-08-17 00:00:00".

Related Skills

• cloud-functions — Cloud function development, deployment, and debugging
• cloudrun-development — CloudRun backend deployment and management
• cloudbase-platform — General platform knowledge and console navigation
• postgresql-development-cloudbase — CloudBase PostgreSQL / PG diagnostics and schema/RLS checks
• relational-database-mcp-cloudbase — MySQL database management and diagnostics
• auth-tool-cloudbase — Auth provider readiness for token failures