canary

Monitor live web apps for console errors, performance regressions, and page failures.

1|Updated Nov 13, 2025
One-click install
npx skills add https://github.com/concept2cure/ClinicalSageAI-2-replit --skill canary-concept2cure
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/concept2cure/ClinicalSageAI-2-replit/tree/main/.claude/skills/gstack/canary
Command: npx skills add https://github.com/concept2cure/ClinicalSageAI-2-replit --skill canary-concept2cure

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-deploy canary monitoring. Watches the live app for console errors, performance regressions, and page failures using the browse daemon. Takes periodic screenshots, compares against pre-deploy baselines, and alerts on anomalies. Use when: "monitor deploy", "canary", "post-deploy check", "watch production", "verify deploy".

Core Features & Use Cases

  • Canary-based health checks that detect console errors, performance regressions, and page failures.
  • Baseline comparison and alerting with automatic screenshots to verify deployment health.
  • Use case: after deploy to production, monitor critical flows and alert on anomalies.

Quick Start

Run canary against your production URL to start monitoring for 10 minutes.

Frequently Asked Questions about canary

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor a production app for issues after a deployment?

To monitor a production app after deployment, use a post-deploy canary runner to continuously check live pages for console errors, performance regressions, and page failures. It compares live screenshots against pre-deploy baselines and alerts on detected anomalies.

What is post-deploy canary monitoring and when should I use it?

Post-deploy canary monitoring is the process of watching a live app for console errors, performance regressions, and page failures immediately after deployment. Use it to verify deployment health and catch critical regressions in production quickly.

Do I need baseline data to detect performance regressions after a release?

Yes, baseline comparison data is required to detect performance regressions after a release. The canary monitor takes periodic screenshots of your live app and compares them against these pre-deploy baselines to surface anomalies quickly.

Does canary monitoring work with a browser daemon to check web page health?

Yes, canary monitoring works with a browse daemon to run browser-based health checks on web pages. It uses this daemon to detect live console errors and page failures, and captures automatic screenshots for rapid remediation.

What is the best way to set up automated alerts for console errors after deploying?

The best way to set up automated alerts for console errors is running a post-deploy canary check against your production URL. It continuously monitors live web pages and outputs alerts with screenshots when anomalies are detected.