Detect production-breaking issues after code deploys using the browse daemon.
npx skills add https://github.com/ajsai47/holyclaude --skill canary-ajsai47
Please help me install this Agent Skill. Skill: canary Source: https://github.com/ajsai47/holyclaude/tree/main/skills/team/canary Command: npx skills add https://github.com/ajsai47/holyclaude --skill canary-ajsai47
Deploys frequently pass all CI checks but still break in production due to issues like missing environment variables, stale CDN caches, or database migrations that perform poorly on real user data. This skill automates post-deploy monitoring to catch these failures in the first 10 minutes after shipping, rather than waiting for user reports hours or days later.
Use the canary skill to monitor your production app at https://your-app.com for 10 minutes immediately after you finish deploying your latest changes.
High-intent search queries and answers about installing and using this skill.
Post-deploy monitoring uses a browse daemon to automatically capture screenshots, collect performance metrics, and check key web pages for console errors or broken links, alerting you to persistent anomalies within minutes of a production deploy.
Deploys pass continuous integration but break in production due to missing environment variables, stale CDN caches, or poor database migrations. Post-deploy verification catches these real-world failures by monitoring live key user pages instead of just running test suites.
You can detect visual regressions after shipping by capturing periodic screenshots of your live web application and comparing them against pre-deploy baselines, spotting visual changes that automated tests might miss.
The best way to catch performance regressions after a code deploy is to run an automated canary check that monitors your live production app for 10 minutes, comparing real-time page load metrics and console errors against pre-deploy baselines.
Automated canary monitoring handles transient network blips by applying severity-based alerting that only alerts on persistent anomalies. It categorizes issues from critical page failures to low-priority new 404s, filtering out temporary network errors.
Yes, deploy verification relies on a browse daemon to access your live production application, capture screenshots, collect performance metrics, and alert on broken links or console errors across key user pages.
shekerkammaMonitor live production deploys for console errors, performance regressions, and page failures.
makyua-sanMonitor production deployments for console errors, performance regressions, and page failures.
luisgustavooliveiraAutomate performance regression detection with browse daemon comparisons.
SnakeODiagnose Angular runtime errors using DevTools, ng.probe, and console utilities.
