What problem does it solve?
Verifying that a newly built feature actually works requires juggling browser testing, API verification, test data setup, and AI output evaluation, which is slow and error-prone when done manually.
Core Features & Use Cases
- Browser QA: Drives the app through the agent-browser CLI with a logged-in Chrome profile, taking screenshots at every step to verify UI behavior, loading states, and error states.
- API and Google Workspace testing: Sets up test data with the gws CLI (Drive files, Gmail messages, Calendar events) and verifies API endpoints with real API keys.
- LLM eval tests: Writes or runs eval tests in
__tests__/eval/ using describeEvalMatrix and judgeMultiple to assess AI output quality, and can persist tests as reusable QA flows.
- Use Case: After implementing a new Smart Filing feature, invoke this skill to spin up the dev server, create a test Drive folder, configure the feature in the browser, trigger it with a test email, and receive a pass/fail report with screenshots.
Quick Start
Ask the assistant to test the feature you just built, for example by saying "test the new bulk archive flow end to end and show me screenshots."