Best use case
canary-watch is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Post-deploy monitoring and canary health verification
Teams using canary-watch should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/canary-watch/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How canary-watch Compares
| Feature / Agent | canary-watch | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Post-deploy monitoring and canary health verification
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Canary Watch — Post-Deploy Monitoring ## When to Use - After deploying to production or staging - After merging a risky PR - When you want to verify a fix actually fixed it - Continuous monitoring during a launch window - After dependency upgrades ## How It Works Monitors a deployed URL for regressions. Runs in a loop until stopped or until the watch window expires. ### What It Watches ``` 1. HTTP Status — is the page returning 200? 2. Console Errors — new errors that weren't there before? 3. Network Failures — failed API calls, 5xx responses? 4. Performance — LCP/CLS/INP regression vs baseline? 5. Content — did key elements disappear? (h1, nav, footer, CTA) 6. API Health — are critical endpoints responding within SLA? ``` ### Watch Modes **Quick check** (default): single pass, report results ``` /canary-watch https://myapp.com ``` **Sustained watch**: check every N minutes for M hours ``` /canary-watch https://myapp.com --interval 5m --duration 2h ``` **Diff mode**: compare staging vs production ``` /canary-watch --compare https://staging.myapp.com https://myapp.com ``` ### Alert Thresholds ```yaml 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?) ``` ### Notifications When a critical threshold is crossed: - Desktop notification (macOS/Linux) - Optional: Slack/Discord webhook - Log to `~/.gemini/canary-watch.log` ## Output ```markdown ## Canary Report — myapp.com — 2026-03-23 03:15 PST ### Status: HEALTHY ✓ | Check | Result | Baseline | Delta | |-------|--------|----------|-------| | HTTP | 200 ✓ | 200 | — | | Console errors | 0 ✓ | 0 | — | | LCP | 1.8s ✓ | 1.6s | +200ms | | CLS | 0.01 ✓ | 0.01 | — | | API /health | 145ms ✓ | 120ms | +25ms | ### No regressions detected. Deploy is clean. ``` ## Integration Pair with: - `/browser-qa` for pre-deploy verification - Hooks: add as a PostToolUse hook on `git push` to auto-check after deploys - CI: run in GitHub Actions after deploy step
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