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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

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Sam-06060/jarvis-assistant
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April 19, 2026 at 13:17
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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
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!
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