canary

Name: canary
Availability: InStock
Author: Mostafa

Monitor live applications for errors and performance issues via screenshot comparison.

3|Updated Oct 12, 2025

Search Tags:#error detection #performance testing #post-deploy #application monitoring #live app monitoring

Ready to run

npx skills add https://github.com/mostafasudo/warpy --skill canary-mostafasudo

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/mostafasudo/warpy/tree/main/.codex/skills/gstack/canary
Command: npx skills add https://github.com/mostafasudo/warpy --skill canary-mostafasudo

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the need for continuous monitoring of live applications post-deployment, ensuring that any issues like console errors, performance regressions, or page failures are detected and addressed promptly.

Core Features & Use Cases

Post-Deploy Monitoring: Continuously watches the live application for errors and performance regressions.
Screenshot Comparison: Takes periodic screenshots and compares them against pre-deploy baselines to detect anomalies.
Alerting: Alerts when anomalies are detected.
Use Case: Ideal for use in CI/CD pipelines to automatically verify the integrity and performance of newly deployed applications.

Quick Start

Run the canary skill to monitor the live application after deployment.

Frequently Asked Questions about canary

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

FAQPage Schema

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

Post-deploy monitoring detects console errors and performance regressions by taking periodic screenshots of the live application and comparing them against pre-deploy baselines to alert on visual or functional anomalies.

How does screenshot comparison detect performance regressions in a live app?▼

Screenshot comparison detects performance regressions by capturing the live application state and matching it against pre-deploy baselines, alerting you when visual or functional anomalies indicate underlying issues.

Can I integrate post-deploy monitoring directly into a CI/CD pipeline?▼

Yes, post-deploy monitoring is ideal for CI/CD pipelines, automatically verifying the integrity and performance of newly deployed applications by continuously watching for errors and regressions.

Do I need Docker and Git to run live app monitoring scripts?▼

Yes, you need Git and Docker for session management and environment setup, while Bash and Python are required to execute the monitoring scripts and browse daemon.

What is the best way to automate anomaly alerts for newly deployed web apps?▼

Automating anomaly alerts involves running a background daemon to continuously monitor the live app, taking screenshots to compare against baselines and triggering alerts when anomalies are detected.