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awt-e2e-testing

awt-e2e-testing

github.com/sickn33Testing & quality48.7k57 installsUpdated today
Repository

About awt-e2e-testing

awt-e2e-testing is a skill for AI coding tools to create YAML browser tests and run them with Playwright. It combines visual matching and OCR with structured failure diagnosis for end-to-end testing.

Key features

  1. 01YAML scenarios executed with Playwright
  2. 02Visual matching with OpenCV and OCR
  3. 03Automatic framework detection
  4. 04Structured failure diagnosis
  5. 05SQLite failure-to-fix patterns

Use cases

  1. 01Test web flows using browser interactions
  2. 02Assert visuals without CSS selectors
  3. 03Investigate end-to-end test failures

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sickn33/agentic-awesome-skills --skill awt-e2e-testing

After installing, type/awt-e2e-testingin Claude Code to confirm it loaded.

Details

From the project README

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

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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