CloudBase Resource Inspection Report Skill

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 (envQuery(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:

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

Inspection Modes

| Mode | When to use | Scope | |------|-------------|-------| | Full inspection | User asks for a general health check / 巡检 / 全面检查 | All resource types + core metrics | | Targeted inspection | User reports a specific error or asks about a specific resource | One resource type or playbook | | Alarm interpretation | User asks CPU 告警是否正常 / 峰值 QPS / 是否限流 | Metrics-first, then logs | | Fault playbook | 429 / function 404 / ACCESS_TOKEN_INVALID / 调用量为 0 | Playbook steps only |

Full Inspection Workflow

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

Step 1 — Environment Check

envQuery(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:

Cloud function errors: queryFunctions(action="listFunctionLogs", functionName="<name>") then queryLogs(action="searchLogs", queryString="* AND functionName:<name> AND level:ERROR", ...)
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.
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
General error search: queryLogs(action="searchLogs", queryString="<error-keyword>", ...)
Alarm / QPS questions: follow references/alarm-interpretation.md
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:

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

Severity Levels

| Level | Icon | Meaning | |-------|------|---------| | Critical | ❌ | Service is down or data is at risk; requires immediate action | | Warning | ⚠️ | Errors detected but service is still partially functional; investigate soon | | Info | ℹ️ | No errors found; informational status only | | Healthy | ✅ | Resource is operating normally |

Preferred Tool Map

| Operation | MCP Tool Call | |-----------|---------------| | Check environment | envQuery(action="info") | | Query metrics (QPS/CPU/invocations) | queryEnv(action="metrics", envId, metricName="...") | | Check CLS status | queryLogs(action="checkLogService") | | List cloud functions | queryFunctions(action="listFunctions") | | Get function detail | queryFunctions(action="getFunctionDetail", functionName="<name>") | | Get function logs | queryFunctions(action="listFunctionLogs", functionName="<name>", startTime="<time>", endTime="<time>") | | Get function log detail | queryFunctions(action="getFunctionLogDetail", requestId="<id>") | | List CloudRun services | queryCloudRun(action="list") | | Get CloudRun detail | queryCloudRun(action="detail", detailServerName="<name>") | | Search CLS logs | queryLogs(action="searchLogs", queryString="<query>", service="tcb\|tcbr", startTime="<time>", endTime="<time>") | | Check NoSQL structure | readNoSqlDatabaseStructure(action="listCollections") | | Check PostgreSQL context | queryPgDatabase(action="context") | | Check PostgreSQL metadata | queryPgDatabase(action="metadata", limit=20) | | Check MySQL status | queryMysqlDatabase(action="getContext") | | Auth provider readiness | queryAppAuth / auth-tool skill (for ACCESS_TOKEN_INVALID) |

Common CLS Query Patterns

| Scenario | queryString | |----------|-------------| | All errors | ERROR | | Function timeout | timeout OR 超时 | | Function OOM | OOM OR out of memory OR 内存超限 | | CloudRun crash | crash OR OOMKilled OR Error | | Specific function errors | functionName:<name> AND level:ERROR | | 5xx HTTP errors | statusCode:>499 | | 429 / throttle | 429 OR throttle OR 限流 OR FREQUENCY | | Function 404 | 404 OR FUNCTION_NOT_FOUND | | Token invalid | ACCESS_TOKEN_INVALID OR token invalid | | Cold start issues | coldStart OR 冷启动 |

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

Agent Skills: CloudBase Resource Inspection Report

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