docs/zh-CN/skills/canary-watch/SKILL.md
使用此技能在部署、合并或依赖升级后监控已部署的URL是否存在回归问题。
npx skillsauth add affaan-m/everything-claude-code canary-watchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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监控已部署 URL 是否存在回归问题。循环运行,直至手动停止或监控窗口过期。
1. HTTP 状态 — 页面是否返回 200?
2. 控制台错误 — 是否出现之前没有的新错误?
3. 网络故障 — 是否存在失败的 API 调用、5xx 响应?
4. 性能 — LCP/CLS/INP 与基线相比是否有退化?
5. 内容 — 关键元素是否消失?(h1、导航、页脚、CTA)
6. API 健康 — 关键端点是否在 SLA 内响应?
快速检查(默认):单次执行,报告结果
/canary-watch https://myapp.com
持续监控:每 N 分钟检查一次,持续 M 小时
/canary-watch https://myapp.com --interval 5m --duration 2h
差异模式:对比预发布环境与生产环境
/canary-watch --compare https://staging.myapp.com https://myapp.com
critical: # immediate alert
- HTTP status != 200
- Console error count > 5 (new errors only)
- LCP > 4s
- API endpoint returns 5xx
warning: # flag in report
- LCP increased > 500ms from baseline
- CLS > 0.1
- New console warnings
- Response time > 2x baseline
info: # log only
- Minor performance variance
- New network requests (third-party scripts added?)
当超过关键阈值时:
~/.claude/canary-watch.log## Canary 报告 — myapp.com — 2026-03-23 03:15 PST
### 状态:健康 ✓
| 检查项 | 结果 | 基线 | 偏差 |
|-------|--------|----------|-------|
| HTTP | 200 ✓ | 200 | — |
| 控制台错误 | 0 ✓ | 0 | — |
| LCP | 1.8s ✓ | 1.6s | +200ms |
| CLS | 0.01 ✓ | 0.01 | — |
| API /health | 145ms ✓ | 120ms | +25ms |
### 未检测到回归问题。部署状态良好。
配合使用:
/browser-qa 进行部署前验证git push 上添加 PostToolUse 钩子,部署后自动检查tools
Garbage collection for your Claude Code configuration. Periodically scans ~/.claude (skills, memory, hooks, permissions, MCP servers, caches) for redundant, stale, orphaned, or low-value items, then walks the user through a confirm-each-deletion cleanup. Use when the user says "clean up my config", "config GC", "too many skills", "audit my setup", "my .claude is bloated", or asks for a periodic config review.
data-ai
当用户希望通过并行工作、并发 agents、批量工具调用、隔离 worktree 或多条独立验证通道来大幅加速任务、同时不损失正确性时使用。
documentation
在回答之前先读取仓库的实时状态,引导用户了解 ECC 当前的 agents、skills、命令、hooks、规则、安装配置档案以及项目接入流程。
testing
Fact-forcing gate that blocks Edit/Write/Bash (including MultiEdit) and demands concrete investigation (importers, data schemas, user instruction) before allowing the action. Measurably improves output quality by +2.25 points vs ungated agents.