gsd-verify-work

Conversational UAT validates built features through plain text dialogue, ensuring functionality aligns with user requirements. It uses conversational AI to interactively test features and track session states for accurate quality assurance diagnosis.

To run user acceptance testing for a specific phase, initiate a conversational test by requesting validation for that phase number. The Skill tracks the test session and outputs results into a structured markdown report named {phase_num}-UAT.md.

Yes, conversational UAT automatically identifies issues during the plain text validation process and prepares structured fix plans. It maintains persistent state throughout the test session to ensure accurate diagnosis of feature functionality gaps.

Yes, persistent state management is required for software testing sessions to accurately track conversational UAT progress and results. It ensures the conversational AI maintains context throughout feature validation for reliable issue diagnosis.

The best way to track UAT results is generating structured markdown reports formatted as {phase_num}-UAT.md. This output tracking captures all test session data, diagnosed issues, and fix plans for quality assurance review.