Add a conservative metadata fixer for missing risk and source fields, cover it with tests, and backfill the remaining skills using explicit source inference only when the provenance is clear. Fall back to the repo-documented defaults when the file does not support a stronger claim. Refs #365
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name, description, risk, source
| name | description | risk | source |
|---|---|---|---|
| awt-e2e-testing | 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 | unknown | https://github.com/ksgisang/awt-skill |
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!