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awt-e2e-testing

Create YAML test scenarios for web applications and run them in a real browser with Playwright. Use image matching and text recognition to check screens, then organize failure findings for investigation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g

연동 도구Playwright
설치 방법 보기

이럴 때 유용합니다

  • Test a checkout flow in a real browser
  • Check screens with image matching and text recognition
  • Investigate browser test failures
  • Test interfaces without stable CSS selectors

포함된 파일(1)

  • SKILL.md3.0 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

AWT — AI-Powered E2E Testing (Beta)

npx skills add ksgisang/awt-skill --skill awt -g

AWT gives AI coding tools the ability to see and interact with web applications through a real browser. Your AI designs YAML test scenarios; AWT executes them with Playwright.

When to Use

  • You need AI-assisted end-to-end testing through a real browser with declarative YAML scenarios.
  • The test flow depends on visual matching, OCR, or platform auto-detection instead of stable DOM selectors.
  • You want an E2E toolchain that can both execute tests and explain failures for AI coding workflows.

Upstream Advertised Capabilities

  • YAML scenarios → Playwright with human-like interaction
  • Visual matching: OpenCV template + OCR (no CSS selectors needed)
  • Platform auto-detection: Flutter, React, Next.js, Vue, Angular, Svelte
  • Structured failure diagnosis with investigation checklists
  • Learning DB: failure→fix patterns in SQLite
  • 5 AI providers: Claude, OpenAI, Gemini, DeepSeek, Ollama
  • Skill Mode: no extra AI API key needed

Execution Boundary

This entrypoint does not bundle the AWT runtime or its YAML schema. Inspect the selected upstream revision and actual installed commands before authoring a scenario. The installation command above is an upstream option, not permission to change global skills. Prefer an explicitly authorized project-scoped installation.

Confirm the target environment, test accounts, permitted browser actions and data retention. A checkout test can place orders or send notifications; use an isolated fixture environment and inspect effects before execution. Do not send screenshots, credentials or application data to a cloud provider without authorization. Record the actual scenario, runtime/version, observed result and artifact paths. If runtime is absent, return a draft and mark execution pending rather than inventing a pass.

Links

Built with the help of AI coding tools — and designed to help AI coding tools test better.

Actively developed by a solo developer at AILoopLab. Feedback welcome!

Example

User request:

Create and run a declarative browser test for the checkout flow, including visual assertions and a clear failure report.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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