canary

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

5|1|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/drt0927/tw-overlay --skill canary-drt0927
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/drt0927/tw-overlay/tree/main/.gemini/skills/gstack-canary
Command: npx skills add https://github.com/drt0927/tw-overlay --skill canary-drt0927

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-deploy canary monitoring fixes the gap between deployment and production stability. It watches a live URL for console errors, performance regressions, and page failures using the browse daemon, takes periodic screenshots, and compares against pre-deploy baselines to alert on anomalies.

Core Features & Use Cases

  • Continuous post-deploy visibility: detects errors, slowdowns, and failed pages after release.
  • Baseline-driven alerts: compares current state to pre-deploy baselines and raises alerts when anomalies are detected.
  • Quick validation: supports configurable duration, pages, and on-demand health checks after deploy events.

Quick Start

Run the canary monitor on the target URL after deployment to observe for 10 minutes with baseline comparisons and alerting.

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 URL for post-deploy production issues?

Post-deploy monitoring tracks a live URL for console errors, performance regressions, and page failures. It uses a browse daemon to take periodic screenshots and compare them against pre-deploy baselines to detect anomalies.

What is canary monitoring and how does it detect application regressions after a release?

Canary monitoring validates application stability after deployment by continuously browsing live URLs. It compares current page states against pre-deploy baselines to automatically detect visual anomalies, console errors, and performance slowdowns.

How do I set up automated baseline comparisons for post-release health checks?

Automated baseline comparisons require running a browse daemon against your target URL after deployment. The daemon takes periodic screenshots, compares them to pre-deploy baselines, and raises anomaly alerts when page failures or regressions occur.

Does post-deploy canary monitoring work without external dependencies?

Post-deploy canary monitoring operates without external dependencies. It uses an internal browse daemon to perform periodic health checks, capture screenshots, and alert on console errors independently after deployment.

What is the best way to get alerts for console errors and page failures after a deploy?

The best way to get alerts for post-deploy page failures is using a canary monitor. It observes a live URL for a configurable duration, detects console errors and performance regressions, and sends anomaly alerts to ensure quick rollback.

When should I use a canary monitor instead of standard production monitoring?

Use a canary monitor immediately after deployment to verify production stability. It specifically compares the current live URL state against pre-deploy baselines for visual regressions and errors, whereas standard monitoring lacks this baseline comparison.