Agent-Skills.md

Agent Skills: AWT — AI-Powered E2E Testing (Beta)

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

UncategorizedID: sickn33/antigravity-awesome-skills/awt-e2e-testing

Repository

sickn33/antigravity-awesome-skills
sickn33License: MIT
27,0474,580

Install this agent skill to your local

pnpm dlx add-skill https://github.com/sickn33/antigravity-awesome-skills/tree/HEAD/skills/awt-e2e-testing

Skill Files

Browse the full folder contents for awt-e2e-testing.

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skills/awt-e2e-testing/SKILL.md

Skill Metadata

Name
awt-e2e-testing
Description
"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"

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.

What works now

  • 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

Links

  • Main repo: https://github.com/ksgisang/AI-Watch-Tester
  • Skill repo: https://github.com/ksgisang/awt-skill
  • Cloud demo: https://ai-watch-tester.vercel.app

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!