Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Use to actually verify a web change in a real browser instead of assuming it works — click through a flow, catch console errors, check a form submits, confirm a fix on the page. Trigger when a UI change needs proof, a bug only reproduces in the browser, or the user asks to test, check, or screenshot the running app.
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Review the instructions the agent will receive before you install.
Code that compiles is not code that works. This is the loop that closes the gap between "the diff looks right" and "the page does the thing".
Drive a real browser against the running app, assert on what actually rendered, and fix what fails. Never report a UI change as working on the strength of the diff alone.
Playwright is the default. It installs its own browsers and runs headless in CI.
npm i -D @playwright/test && npx playwright install chromium
Start the app first and hold the port — a test suite against a dead server produces a wall of timeouts that tells you nothing:
npm run dev > /tmp/dev.log 2>&1 &
npx wait-on http://localhost:3000
const errors = []
page.on('console', m => m.type() === 'error' && errors.push(m.text()))
page.on('pageerror', e => errors.push(e.message))
// ... drive the flow ...
expect(errors).toEqual([])
Query the way a person looks at a page: role, label, and visible text. getByRole('button', { name: 'Send' }) survives a restyle; .btn-primary > span:nth-child(2) does not. Add data-testid only where the visible text is genuinely ambiguous.
Take one on failure automatically, and one at the end of a flow when a human needs to eyeball the result. Full-page for layout questions, element-scoped for a component. Save under /tmp unless the user wants them kept.
npx playwright test --reporter=line 2>&1 | tail -30
Pipe the output. A full Playwright HTML reporter dump is thousands of tokens of nothing.
| Symptom | Real cause |
|---|---|
| Every test times out | App never started, or wrong port |
| Passes locally, fails headless | Animation or viewport size, not logic |
| Flaky on CI only | Waiting on a timeout instead of a condition |
| Blank page, no error | Client-side exception swallowed by an error boundary |
| Works once, fails on re-run | Test wrote state it never cleaned up |
Never fix flake with waitForTimeout. Wait for the condition — a selector, a response, a URL.
Say what flow was driven, what was asserted, and the result. If something is still unverified, name it. Screenshots go with the answer when the question was visual.
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Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.
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Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
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Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
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Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
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Designs and deploys custom agent teams for specific business workflows. Interactive discovery of business processes, then generates complete team configurations with specialized agent roles, tool access, communication protocols, and handoff rules.
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Agent-to-Agent (A2A) communication protocol. Connect two or more Claude agents that pass messages, share context, delegate tasks, and collaborate. Implements structured handoffs, shared memory, and multi-agent conversations.
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