awt-e2e-testing – Coding skill for AI agents
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
Install the awt-e2e-testing skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/awt-e2e-testing-4e805.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /awt-e2e-testing – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/awt-e2e-testing-4e805.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $awt-e2e-testing – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/awt-e2e-testing-4e805.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /awt-e2e-testing – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/awt-e2e-testing-4e805.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /awt-e2e-testing – then describe the task you want done.
SKILL.md content
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.
Upstream Advertised Capabilities
- 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
Execution Boundary
This entrypoint does not bundle the AWT runtime or its YAML schema. Inspect the selected upstream revision and actual installed commands before authoring a scenario. The installation command above is an upstream option, not permission to change global skills. Prefer an explicitly authorized project-scoped installation.
Confirm the target environment, test accounts, permitted browser actions and data retention. A checkout test can place orders or send notifications; use an isolated fixture environment and inspect effects before execution. Do not send screenshots, credentials or application data to a cloud provider without authorization. Record the actual scenario, runtime/version, observed result and artifact paths. If runtime is absent, return a draft and mark execution pending rather than inventing a pass.
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!
Example
User request:
> Create and run a declarative browser test for the checkout flow, including visual assertions and a clear failure report.
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.
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