canary

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

Updated Apr 8, 2026

Search Tags:#performance #monitoring #application stability #canary #post-deploy

Ready to run

npx skills add https://github.com/sadie100/claude-dotfiles --skill canary-sadie100

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/sadie100/claude-dotfiles/tree/main/skills/canary
Command: npx skills add https://github.com/sadie100/claude-dotfiles --skill canary-sadie100

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Python, and includes scripts (resource) components.

What problem does it solve?

This Skill automates post-deploy monitoring to detect issues in live applications. It tracks console errors, performance regressions, and page failures, providing periodic screenshots and alerts on anomalies.

Core Features & Use Cases

Post-Deployment Monitoring: Monitors the live app for issues such as console errors and performance regressions.
Screenshot Comparison: Periodically takes screenshots and compares them against pre-deploy baselines.
Alerting: Notifies of any detected anomalies.
Use Case: Ideal for ensuring the stability of deployed applications by promptly identifying and addressing potential issues.

Quick Start

Run the 'canary' skill to initiate post-deploy monitoring on the live application.

Frequently Asked Questions about canary

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

FAQPage Schema

How do I monitor live applications for console errors after a deployment?▼

Post-deploy monitoring tracks live applications for console errors and page failures after deployment. It utilizes browsing daemons and automated scripts to detect anomalies and trigger alerts when issues are found.

What is automated screenshot comparison for post-deploy application stability?▼

Automated screenshot comparison captures periodic screenshots of a live application and compares them against pre-deploy baselines. This visual regression check detects unexpected page failures or layout shifts following a deployment.

Can I detect performance regressions in my live app using Bash and Python scripts?▼

Yes, you can detect performance regressions using Bash and Python scripts. The monitoring process runs these scripts to continuously check the live application and alert you when a performance drop or anomaly is detected.

What's the best way to set up post-deploy alerts for application stability issues?▼

The best way to set up post-deploy alerts for application stability is to run an automated monitoring process that tracks console errors and performance regressions. It triggers alerts immediately upon detecting any anomalies in the live environment.

Does post-deploy canary monitoring work with existing browsing daemons?▼

Yes, post-deploy canary monitoring works with browsing daemons. It uses them alongside Bash and Python scripts to capture screenshots, compare visual baselines, and track live application stability for performance regressions.

When do I need to run automated post-deploy monitoring on my application?▼

You need to run automated post-deploy monitoring immediately after releasing new code to a live environment. It ensures application stability by promptly identifying console errors, performance regressions, and page failures before users are impacted.