Specify a webhook-driven task for OpenClaw
Describe event inputs, validation, deduplication, and intended actions before integration work.
5,441,677 AI resources indexedWorking toward the world’s largest AI resource index.
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
--- name: awt-e2e-testing-67dfb03f10f1 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" risk: unknown source: "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! ## 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.--- name: awt-e2e-testing-67dfb03f10f1 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" risk: unknown source: "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! ## 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.
Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.