本文へ移動
cccskills
無料GitHub で公開

browser-test-loop

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.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md3.5 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Browser Test Loop

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".

Core Behavior

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.

Setup

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

The Loop

  1. Name the assertion in one sentence. "After submitting the contact form with a valid email, a success message appears and no console error fires." Vague goals produce vague tests.
  2. Write the smallest script that proves it. One flow per file.
  3. Run it. Read the failure, not the summary.
  4. Fix the app, not the test — unless the test encoded the wrong expectation, in which case say so out loud.
  5. Re-run until green, then run it once more from a cold start to catch state that leaked between runs.

What to Assert

  • The user-visible outcome: text on screen, a URL change, a row that appeared.
  • Zero unexpected console errors. Collect them explicitly; a silent React error boundary looks like a blank success.
  • Network calls that should have fired, and their status codes.
  • The empty, loading, and error states — not just the happy path.
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([])

Selector Rules

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.

Screenshots

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.

Common Failure Modes

SymptomReal cause
Every test times outApp never started, or wrong port
Passes locally, fails headlessAnimation or viewport size, not logic
Flaky on CI onlyWaiting on a timeout instead of a condition
Blank page, no errorClient-side exception swallowed by an error boundary
Works once, fails on re-runTest wrote state it never cleaned up

Never fix flake with waitForTimeout. Wait for the condition — a selector, a response, a URL.

Reporting

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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Audit websites for accessibility issues and WCAG compliance. Use when checking accessibility, fixing a11y issues, or ensuring WCAG compliance.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

OneWave-AI/claude-skills3362026年10月2日 更新

OneWave-AI のスキルをすべて見る

このスキルの問題を報告する