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canary

Monitors deployed applications for console errors, performance regressions, and page failures.

Updated Jun 22, 2026
Search Tags:#monitoring#deployment#screenshots#production#regression#canary#gstack
One-click install
npx skills add https://github.com/aicodepro/ai-agent-nexi --skill canary-aicodepro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/aicodepro/ai-agent-nexi/tree/main/agent/skills/gstack/canary
Command: npx skills add https://github.com/aicodepro/ai-agent-nexi --skill canary-aicodepro

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? After a deployment, teams need to know quickly whether the live app is broken. This Skill watches the production app for console errors, performance regressions, and page failures so problems are caught before users report them. ## Core Features & Use Cases - Post-deploy monitoring: Watches the live app through a browse daemon, capturing console errors and page failures as they occur. - Visual regression detection: Takes periodic screenshots and compares them against pre-deploy baselines to flag unexpected visual changes. - Anomaly alerting: Alerts on anomalies detected during the monitoring window so regressions surface immediately. - Use Case: After shipping a new release, invoke the canary monitor to watch production for a period, comparing live behavior and screenshots against the pre-deploy baseline and alerting if anything diverges. ## Quick Start Ask the assistant to run the canary skill to monitor the deployed app for errors and regressions after the next deploy.

Frequently Asked Questions about canary

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

FAQPage Schema
How do I monitor my app after a deployment?▼

Invoke the canary skill after deploying. It watches the live app through the browse daemon, capturing console errors, performance regressions, and page failures, and alerts you when anomalies appear.

How does canary detect visual regressions in production?▼

It takes periodic screenshots of the live app and compares them against pre-deploy baselines. Differences between the current capture and the baseline are flagged as anomalies for review.

What kinds of issues does post-deploy canary monitoring catch?▼

It catches console errors, performance regressions, and page failures observed in the live app, plus visual differences detected by screenshot comparison against the pre-deploy baseline.

When should I use canary monitoring instead of pre-deploy testing?▼

Use it after deployment to verify real production behavior. Pre-deploy testing validates changes before release; canary monitoring confirms the live app stays healthy and alerts on issues that only appear in production.

What triggers canary monitoring alerts?▼

Alerts fire on anomalies detected during the watch window, including new console errors, page failures, performance regressions, and screenshot mismatches against the pre-deploy baseline.

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