AWT — Eyes and Hands for Your AI Coding Tool

Your AI coding tool is smart. But it can't see or click a web page. AWT gives it a real browser — so it can test, find bugs, and fix them without you lifting a finger.

Works without AI API — write YAML scenarios manually and run aat run. No API key needed. AI coding tools make it easier, but are not required.

What is AWT?

AWT is the execution engine for AI-powered E2E testing. Your AI coding tool designs the tests; AWT runs them in a real browser with Playwright.

How it works in Skill Mode (no extra AI API key needed):

You: "Test the login flow on https://mysite.com"

Your AI coding tool:
  → Writes 5 YAML scenarios (30 steps)
  → Runs: aat run scenarios/
  → Reads failure: "Step 4: Dashboard text not visible"
  → Reads screenshot + source code
  → Fixes src/pages/login.js:23
  → Re-runs: aat run scenarios/
  → All 5 scenarios pass ✓

Key capabilities:

• Execute tests in a real browser with human-like mouse/keyboard interaction
• See — take screenshots, detect elements via OCR and image matching
• Report — step-by-step pass/fail with error details and screenshots
• Self-heal (CLI mode) — aat loop auto-fixes failures with its own AI
• Learn — successful matches stored in SQLite, getting faster over time

Installation

One-line install (recommended)

npx skills add ksgisang/awt-skill --skill awt -g

Manual Installation

git clone https://github.com/ksgisang/awt-skill.git /tmp/awt-skill
cp -r /tmp/awt-skill/awt ~/.claude/skills/awt
rm -rf /tmp/awt-skill

Per-Project Installation

git clone https://github.com/ksgisang/awt-skill.git /tmp/awt-skill
cp -r /tmp/awt-skill/awt .claude/skills/awt
rm -rf /tmp/awt-skill

After installation, the skill auto-triggers on testing-related prompts.

Updating

# Re-run the same install command to get the latest version
npx skills add ksgisang/awt-skill --skill awt -g -y

For manual installations: cd ~/.claude/skills/awt && git pull

Comparison with Other Testing Skills

When to use each:

• webapp-testing — Quick one-off Playwright scripts for simple page checks
• playwright-skill — When you need fine-grained Playwright API control
• AWT Skill Mode — Your AI coding tool designs tests, AWT executes them. No extra AI API key needed.
• AWT CLI Mode — Standalone automated testing with aat generate + aat loop for CI/CD

Supported AI Coding Tools

AWT follows the Agent Skills open standard and works with:

Quick Example

YAML Scenario

id: "SC-001"
name: "User Login"
tags: ["auth", "login"]
depends_on: ["SC-000"]
steps:
  - step: 1
    action: navigate
    value: "{{url}}/login"
    description: "Go to login page"

  - step: 2
    action: find_and_type
    target:
      text: "Email"
      match_method: ocr
    value: "test@example.com"
    humanize: true
    description: "Enter email"

  - step: 3
    action: find_and_click
    target:
      text: "Login"
    description: "Click login button"

  - step: 4
    action: assert
    assert_type: text_visible
    expected:
      - type: text_visible
        value: "Welcome back"
    description: "Verify login success"

Natural Language (in Claude Code)

"Login to mysite.com with test@example.com, then check if the dashboard loads"

AWT converts this to a YAML scenario and executes it automatically.

5-Step DevQA Workflow

Scan → Plan → Review → Execute → Heal
  ↑                                 |
  └─── Loop back on failure ────────┘

1. Scan — Crawl site, analyze DOM, detect features
2. Plan — AI generates YAML test scenarios
3. Review — User reviews/edits before execution
4. Execute — Playwright runs with live screenshots
5. Heal — AI analyzes failure → suggests fix → re-tests

AI Providers

Project Structure

awt-skill/
├── awt/                        # ← Skill content (installed by npx skills)
│   ├── SKILL.md                # Main skill definition
│   ├── references/
│   │   ├── scenario-schema.md  # Full YAML schema reference
│   │   ├── cli-reference.md    # CLI command reference
│   │   └── config-reference.md # Configuration options
│   └── templates/
│       ├── scenario-template.yaml
│       └── config-template.yaml
├── README.md
├── LICENSE
├── CONTRIBUTING.md
└── package.json

Key CLI Commands

System Dependencies

macOS:

brew install python@3.12 tesseract
pipx install aat-devqa
playwright install chromium

Linux (Ubuntu/Debian):

sudo apt install python3.12 python3.12-venv tesseract-ocr
pipx install aat-devqa
playwright install chromium

Windows:

winget install Python.Python.3.12
choco install tesseract
pip install aat-devqa
playwright install chromium

After install, run aat doctor to verify everything works.

Links

• Main Repository: github.com/ksgisang/AI-Watch-Tester
• Cloud Demo: ai-watch-tester.vercel.app
• Agent Skills Standard: agentskills.io

License

AGPL-3.0 — see LICENSE file for full text.

Built by AILoopLab.