What problem does it solve? Verifying that a web application's UI actually meets acceptance criteria requires controlled browser interaction and durable evidence, which is hard to do consistently inside an automated SDLC workflow. ## Core Features & Use Cases - Harness-aware browser control: Runs the declared harness, using human-like computer-use when the evaluation plan requires it, or Browser/Playwright MCP otherwise. - Evidence capture: Records screenshots, accessibility snapshots, and console or network notes at meaningful checkpoints, refreshing accessibility state after every action. - Failure classification: Maps failures to ENVIRONMENT_DEFECT, EVALUATION_DEFECT, TEST_DEFECT, or SPEC_GAP so the workflow can route correctly. - Use Case: During an Agentic SDLC run, a feature's UAT plan requires human-like computer-use; the coordinator invokes this skill to drive the app, capture evidence, and return a pass/fail result. ## Quick Start Ask the Agentic SDLC coordinator to run the GUI evaluation for the active feature using the declared harness and record evidence under the current run directory.