Ops Inspector
AIOps-style CloudBase inspection skill.
Install
npx skills add TencentCloudBase/CloudBase-AI-Toolkit --skill ops-inspector -g -a claude-code -y- Repository
- TencentCloudBase/CloudBase-AI-Toolkit1.2k
- Category
- Engineering
- Updated
- 3d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
AIOps-style CloudBase inspection skill. Use when users need 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, or a scheduled patrol that reports only new or worse findings. Triggers on 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.
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 fault playbook: 429 / 限频, AI 模型 429 / Token 额度, 云函数超时或轮询超时（
-404005/433）, 云函数 404, ACCESS_TOKEN_INVALID, or 调用量为 0. - The user wants a patrol rather than a one-off check ("每天帮我看看有没有变差", "定时巡检", "值守"), or asks to put an inspection on a schedule.
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.
