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canary-watch

Use this skill to monitor and verify a deployed URL after releases — checks HTTP endpoints, SSE streams, static assets, console errors, and performance regressions after deploys, merges, or dependency upgrades. Smoke / canary / post-deploy verification.

O que é canary-watch?

canary-watch is a Claude Code agent skill that use this skill to monitor and verify a deployed URL after releases — checks HTTP endpoints, SSE streams, static assets, console errors, and performance regressions after deploys, merges, or dependency upgrades. Smoke / canary / post-deploy verification.

Funciona comClaude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/canary-watch

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Documentação

Canary Watch — Post-Deploy Monitoring

When to Use

  • After deploying to production or staging
  • After merging a risky PR
  • When you want to verify a fix actually fixed it
  • Continuous monitoring during a launch window
  • After dependency upgrades

How It Works

Monitors a deployed URL for regressions. Runs in a loop until stopped or until the watch window expires.

What It Watches

1. HTTP Status — is the page returning 200?
2. Console Errors — new errors that weren't there before?
3. Network Failures — failed API calls, 5xx responses?
4. Performance — LCP/CLS/INP regression vs baseline?
5. Content — did key elements disappear? (h1, nav, footer, CTA)
6. API Health — are critical endpoints responding within SLA?
7. Static Assets — are JS, CSS, image, and font requests returning 2xx/3xx with expected content types?
8. SSE Streams — do event-stream endpoints connect and receive an initial event or heartbeat?

Watch Modes

Quick check (default): single pass, report results

/canary-watch https://myapp.com

Sustained watch: check every N minutes for M hours

/canary-watch https://myapp.com --interval 5m --duration 2h

Diff mode: compare staging vs production

/canary-watch --compare https://staging.myapp.com https://myapp.com

Alert Thresholds

critical:  # immediate alert
  - HTTP status != 200
  - Console error count > 5 (new errors only)
  - LCP > 4s
  - API endpoint returns 5xx
  - Static asset returns 4xx/5xx
  - SSE endpoint cannot connect or drops before first heartbeat

warning:   # flag in report
  - LCP increased > 500ms from baseline
  - CLS > 0.1
  - New console warnings
  - Response time > 2x baseline
  - Static asset content type changed unexpectedly
  - SSE heartbeat latency > 2x baseline

info:      # log only
  - Minor performance variance
  - New network requests (third-party scripts added?)

Notifications

When a critical threshold is crossed:

  • Desktop notification (macOS/Linux)
  • Optional: Slack/Discord webhook
  • Log to ~/.claude/canary-watch.log

Output

## Canary Report — myapp.com — 2026-03-23 03:15 PST

### Status: HEALTHY ✓

| Check | Result | Baseline | Delta |
|-------|--------|----------|-------|
| HTTP | 200 ✓ | 200 | — |
| Console errors | 0 ✓ | 0 | — |
| LCP | 1.8s ✓ | 1.6s | +200ms |
| CLS | 0.01 ✓ | 0.01 | — |
| API /health | 145ms ✓ | 120ms | +25ms |
| Static assets | 42/42 ✓ | 42/42 | — |
| SSE /events | connected ✓ | connected | +80ms heartbeat |

### No regressions detected. Deploy is clean.

Integration

Pair with:

  • /browser-qa for pre-deploy verification
  • Hooks: add as a PostToolUse hook on git push to auto-check after deploys
  • CI: run in GitHub Actions after deploy step

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

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affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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