canary

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

Updated Aug 27, 2026

Search Tags:#performance #monitoring #baseline #browse #canary #post-deploy

Ready to run

npx skills add https://github.com/gfires/motion-analysis --skill canary-gfires

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/gfires/motion-analysis/tree/main/canary
Command: npx skills add https://github.com/gfires/motion-analysis --skill canary-gfires

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-deploy canary monitoring watches the live app for console errors, performance regressions, and page failures. It uses a browse daemon to capture baselines, run health checks, and alert on anomalies during the post-deploy window.

Core Features & Use Cases

Post-deploy health monitoring that surfaces console errors, slow pages, and UI failures.
Baseline capture and regression checks using the browse daemon to compare current state against pre-deploy baselines.
Use Case: After deploying a new version, run canary monitoring to quickly surface regressions before user impact.

Quick Start

Start monitoring a URL by invoking /canary with the target URL and optional flags to define duration, pages, or baseline capture.

Frequently Asked Questions about canary

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

FAQPage Schema

What is post-deploy canary monitoring and how does it verify production health?▼

Post-deploy canary monitoring watches the live app for console errors, performance regressions, and page failures during the monitoring window. It compares current state against pre-deploy baselines to verify deploy quality.

How do I monitor my live application for performance regressions after a deployment?▼

You can monitor live application performance regressions by invoking the canary monitoring tool with a target URL. It uses a browse daemon to capture baselines, run health checks, and alert on anomalies during the post-deploy window.

Can I compare current live application state against pre-deploy baselines?▼

Yes, the canary monitoring process uses a browse daemon to capture baseline screenshots and compare them against pre-deploy baselines. It automatically alerts on anomalies like UI failures and slow pages during the monitoring window.

How do I capture pre-deploy baselines for post-deploy health monitoring?▼

Pre-deploy baselines are captured using the browse daemon, which takes baseline screenshots of target pages. The skill coordinates setup, baseline capture, page discovery, and health checks to verify deploy quality.

Does canary monitoring work without setting up a browse daemon?▼

No, the browse daemon is required. It is the core component used to take baseline screenshots, run health checks, discover pages, and alert on anomalies during the post-deploy monitoring window.

What types of production anomalies does post-deploy canary monitoring surface?▼

Post-deploy canary monitoring surfaces console errors, performance regressions, and page failures. It alerts on these anomalies during the monitoring window to quickly identify regressions before user impact.