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canary

Monitor live applications for console errors, performance issues, and failures post-deployment.

Updated Jun 9, 2026
Search Tags:#error detection#monitoring#performance analysis#deployments#app stability
One-click install
npx skills add https://github.com/ericdahl-dev/coauthor-cleaner --skill canary-ericdahl-dev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/ericdahl-dev/coauthor-cleaner/tree/main/.claude/skills/gstack/canary
Command: npx skills add https://github.com/ericdahl-dev/coauthor-cleaner --skill canary-ericdahl-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Write, Glob, AskUserQuestion, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides continuous monitoring of live apps for errors, performance regressions, and failures, offering periodic screenshots for anomaly detection post-deployment.

Core Features & Use Cases

  • App Health Monitoring: Watches live app for console errors, performance regressions, and page failures.
  • Automated Alerts: Sends alerts on anomalies detected, including screenshots and pre-deploy baselines.
  • Use Case: Utilize the canary skill to monitor the stability of your application immediately after deployment and catch any issues before they impact end-users.

Quick Start

Activate the canary skill for your deployment to ensure continuous monitoring of the application post-deployment.

Frequently Asked Questions about canary

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

FAQPage Schema
How do I monitor app stability and detect errors after a deployment?▼

Post-deploy monitoring tracks live applications to detect console errors, performance regressions, and page failures. It continuously watches app health immediately after deployment to catch issues before they impact end-users.

What is the best way to detect performance regressions in a live application?▼

Live app monitoring collects performance metrics and captures periodic screenshots for anomaly detection. It compares post-deploy states against pre-deploy baselines to identify regressions and alert on failures.

Can I use automated alerts and screenshot comparisons for anomaly detection in production?▼

Yes, post-deploy monitoring operates in production environments with pre-defined deployment scenarios to send automated alerts on detected anomalies. It uses periodic screenshot comparisons alongside console logging and performance metrics collection.

How do I set up continuous monitoring for live apps to catch console errors and failures?▼

Activate post-deploy monitoring for your deployment to ensure continuous monitoring of the live application. The system uses tools for console logging, performance metrics collection, and error alerting systems to verify app health.

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