canary

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

Updated Mar 14, 2026
One-click install
npx skills add https://github.com/EhsaanArk/ai-signal-router --skill canary-ehsaanark
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/EhsaanArk/ai-signal-router/tree/main/.claude/skills/gstack/canary
Command: npx skills add https://github.com/EhsaanArk/ai-signal-router --skill canary-ehsaanark

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Monitors production after deployment to detect issues that CI may miss, such as console errors, performance regressions, and page failures.

Core Features & Use Cases

  • Real-time post-deploy monitoring of a live URL with baseline comparison and automated alerts.
  • Per-page canary checks, configurable pages, baseline capture, and health reporting for audits.
  • Supports long-running monitoring sessions, baseline updates, and structured canary reports for reviews.

Quick Start

Invoke /canary with a target URL to start a 10-minute post-deploy verification.

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?

Monitor a live URL for post-deploy production issues by running an automated canary workflow that checks for console errors, performance regressions, and page failures against a captured baseline. Invoke /canary with the target URL to start verification.

What is canary monitoring and when do I need it for deployment reliability?

Canary monitoring is an automated post-deploy verification process that continuously checks a live URL for console errors and performance regressions. You need it to detect production issues that CI pipelines may miss after deployment.

Do I need a browse daemon to run post-deploy canary checks?

Yes, you need a browse daemon and accessible canary tooling to run post-deploy checks. The workflow relies on these components to continuously monitor the live URL and output structured artifacts like baseline.json and canary reports.

How do I capture a baseline for visual regression and performance monitoring?

Capture a baseline for visual regression and performance monitoring by running the canary workflow against your target pages before deployment. This generates a baseline.json artifact used to validate health and compare future page states.

Can I run long-running monitoring sessions across multiple pages?

Yes, you can run long-running monitoring sessions across multiple pages. The canary workflow supports configurable per-page checks, baseline updates, and structured canary reports for ongoing post-deploy health reviews.