canary

Monitor production URLs for errors, performance regressions, and broken pages.

46|13|Updated Jul 30, 2025

Search Tags:#monitoring #screenshots #production #telemetry #baseline #deploy #canary

Ready to run

npx skills add https://github.com/aimasteracc/tree-sitter-analyzer --skill canary-aimasteracc

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: canary
Source: https://github.com/aimasteracc/tree-sitter-analyzer/tree/main/.claude/skills/canary
Command: npx skills add https://github.com/aimasteracc/tree-sitter-analyzer --skill canary-aimasteracc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-deploy reliability often suffers from silent failures such as console errors, performance regressions, and broken pages that slip through CI. Canary monitoring helps catch these issues in production by continuously observing a live URL, capturing browser metrics, and comparing against pre-deploy baselines.

Core Features & Use Cases

Continuously monitor a production URL for errors, latency spikes, and page failures using the browse daemon.
Take baseline screenshots and build a reference manifest to detect regressions after deploy.
Generate alerts and health summaries when anomalies are detected, enabling rapid rollback or remediation.
Use after deployment to verify release health across multiple pages and scenarios.

Quick Start

Run canary after deployment to monitor production for 10 minutes.

Frequently Asked Questions about canary

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

FAQPage Schema

How do I monitor production deployments for silent failures like console errors and performance regressions?▼

Canary monitoring catches silent production failures by continuously observing a live URL for errors, latency spikes, and broken pages. It uses the browse daemon to capture browser metrics and compares them against pre-deploy baselines to detect regressions.

What is post-deploy canary monitoring and how does it work?▼

Post-deploy canary monitoring is the process of verifying release health by watching a live production URL. It applies baseline comparisons across pages, capturing screenshots and telemetry to identify anomalies that slip through CI, producing alerts and a health summary.

How do I verify release health across multiple pages after a deploy?▼

You can verify release health by configuring multiple canary checks across various pages. The monitoring process watches the live URLs for performance regressions and broken pages, generating a comprehensive health summary based on observed changes.

Do I need a browse daemon to take baseline screenshots for canary checks?▼

Yes, the browse daemon is required to continuously monitor the production URL and capture baseline screenshots. This baseline data builds a reference manifest used to detect page failures and performance regressions after deployment.

What is the best way to detect broken pages and latency spikes in production?▼

The best way to detect broken pages and latency spikes is continuous live URL monitoring with baseline comparisons. By capturing browser metrics and comparing them against a pre-deploy baseline, you can generate immediate alerts when anomalies occur.