houseofmvps/ultraship/canary

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  • ext:[{"type":"hook","description":"Pre/post lifecycle hooks"}]
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Post-deploy canary monitoring — checks site health, detects regressions, monitors for errors after deployment. Use after deploying to verify production is healthy.

Install

npx vskill@latest install houseofmvps/ultraship/canary

Semi-extensibleMentions customization, but needs skill-specific knowledge. Read the extensible skills standard

SKILL.md

Post-Deploy Canary Monitor

After every deploy, canary monitoring verifies your production site is healthy. It checks HTTP status, response time, error patterns, and compares against a baseline to detect regressions.

Announce at start: "I'm running post-deploy canary monitoring."

Process

Step 1: Run Canary Checks
bash
node ${CLAUDE_PLUGIN_ROOT}/tools/canary-monitor.mjs <production-url> --checks 3 --interval 2

This runs 3 health checks with 2-second intervals. Options:

  • --checks N — number of checks to run (default: 3)
  • --interval S — seconds between checks (default: 2)
  • --baseline <file> — path to baseline file for regression comparison
Step 2: Analyze Results

The canary monitor returns a health status:

StatusMeaningAction
healthyAll checks pass, no regressionsDeploy succeeded
degradedSite is up but has error patterns or issuesInvestigate the specific issues
regression_detectedPerformance or behavior regressed from baselineCompare with baseline, consider rollback
critical_regressionMajor regression (status code change, 3x slower)Rollback immediately
downSite is unreachable or returning errorsRollback immediately, use /rescue
Step 3: Report

Present the results clearly:

+===========================================+
| C A N A R Y R E P O R T |
+===========================================+
| URL savemrr.co |
| Status ✓ HEALTHY |
| Response Time 234ms (avg) |
| Checks 3/3 passed |
| Regressions None |
+===========================================+

If issues are found, show them with severity and recommended action.

Step 4: If Unhealthy

If the canary detects problems:

If a Sentry MCP server is connected (check your available tools for sentry), confirm the regression against live error data: compare the error/issue rate since this deploy to the prior baseline window. A post-deploy spike in a new issue is hard confirmation that the deploy caused it — and the stack trace tells you exactly what to roll back or fix. Distinguish a real regression from background noise this way before recommending a rollback.

  1. `degraded` — Show the specific error patterns found. Check if they're pre-existing or new.
  2. `regression_detected` — Show the before/after comparison. If response time regressed >50%, investigate.
  3. `critical_regression` or `down` — Recommend immediate rollback:

``bash git revert HEAD --no-edit && git push ` Then use /rescue` for full incident diagnosis.

Step 5: Save Baseline

When the site is healthy, the canary automatically saves a baseline to .ultraship/canary/baseline.json. Future canary runs compare against this baseline to detect regressions.

Continuous Monitoring Loop

For extended monitoring after a risky deploy:

bash
node ${CLAUDE_PLUGIN_ROOT}/tools/canary-monitor.mjs <url> --checks 10 --interval 30

This runs 10 checks over 5 minutes, catching delayed failures (connection pool exhaustion, memory leaks, cache warm-up issues).

Integration with Other Skills

  • `/deploy` — Run canary automatically after deploy completes
  • `/rescue` — If canary detects down or critical_regression, escalate to incident response
  • `/retro` — Include canary results in sprint retrospectives
  • `/learn` — Save deployment gotchas as learnings when canary catches issues

Playwright Browser Checks (Optional)

For deeper verification, combine canary with Playwright MCP:

  1. Navigate to the production URL
  2. Take a screenshot
  3. Check for console errors via browser_console_messages
  4. Verify key user flows (login, main feature) work
  5. Compare screenshots with pre-deploy captures (via /visual-diff)

This catches JavaScript errors, broken layouts, and functional regressions that HTTP-only checks miss.

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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Source

Popularity

Repository stars
116
Repository forks
13
Repository npm downloads, 7 days
22
7-day trend score
39

Stars and forks are for the whole GitHub repository, not this skill alone. Downloads are for the repository's npm package. Refreshed 29 Apr 2026, 5 months ago.

Extension points

  • hookPre/post lifecycle hooks

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