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* fix: stabilize validation and tests on Windows * test: add Windows smoke coverage for skill activation * refactor: make setup_web script CommonJS * fix: repair aegisops-ai frontmatter * docs: add when-to-use guidance to core skills * docs: add when-to-use guidance to Apify skills * docs: add when-to-use guidance to Google and Expo skills * docs: add when-to-use guidance to Makepad skills * docs: add when-to-use guidance to git workflow skills * docs: add when-to-use guidance to fp-ts skills * docs: add when-to-use guidance to Three.js skills * docs: add when-to-use guidance to n8n skills * docs: add when-to-use guidance to health analysis skills * docs: add when-to-use guidance to writing and review skills * meta: sync generated catalog metadata * docs: add when-to-use guidance to Robius skills * docs: add when-to-use guidance to review and workflow skills * docs: add when-to-use guidance to science and data skills * docs: add when-to-use guidance to tooling and automation skills * docs: add when-to-use guidance to remaining skills * fix: gate bundle helper execution in Windows activation * chore: drop generated artifacts from contributor PR * docs(maintenance): Record PR 457 sweep Document the open issue triage, PR supersedence decision, local verification, and source-only cleanup that prepared PR #457 for re-running CI. --------- Co-authored-by: sickn33 <sickn33@users.noreply.github.com>
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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.
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.
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!