canary

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

9|3|Updated Jan 29, 2022
One-click install
npx skills add https://github.com/I194/PMTools_2.0 --skill canary-i194
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/I194/PMTools_2.0/tree/main/.claude/skills/gstack/canary
Command: npx skills add https://github.com/I194/PMTools_2.0 --skill canary-i194

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

After deployment, subtle issues can slip into production. This Skill provides continuous, automated watch to surface console errors, performance regressions, and page failures before users notice them.

Core Features & Use Cases

  • Live monitoring of the deployed app to detect errors and regressions.
  • Periodic screenshots and visual comparisons against pre-deploy baselines.
  • Alerts when anomalies are detected, with quick triage for remediation.

Quick Start

Start monitoring a URL by invoking the canary skill with your deployment URL and optional duration.

Frequently Asked Questions about canary

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

FAQPage Schema
How do I monitor my production app for issues after a deployment?

Post-deploy monitoring uses a browse daemon to watch your live app, taking periodic screenshots and comparing them against pre-deploy baselines to surface console errors, performance regressions, and page failures before users notice them.

What is canary monitoring and when do I need it?

Canary monitoring is the continuous, automated watch of a deployed application to detect subtle issues that slip into production. You need it during deploy, canary, post-deploy check, and verify deploy workflows to catch anomalies early.

How do I start monitoring a URL for production regressions?

Start monitoring a deployment URL by invoking the canary skill with your URL and an optional duration parameter. The browse daemon will then take periodic screenshots and compare them against pre-deploy baselines to detect anomalies.

Can I get alerts when performance regressions or console errors appear in production?

Yes, alerts are triggered when anomalies such as console errors, performance regressions, or page failures are detected during live monitoring, providing quick triage information for remediation.

Do I need pre-deploy baselines to detect production issues?

Yes, pre-deploy baselines are required. The skill compares periodic screenshots taken from the live app against these baselines to visually surface anomalies and detect regressions after deployment.

What's the best way to catch page failures before users notice them?

Automated post-deploy monitoring is the best approach, using a browse daemon to continuously watch the live app, compare screenshots against baselines, and alert on console errors, performance regressions, and page failures for quick triage.