gsd-verify-work

Name: gsd-verify-work
Availability: InStock
Author: zerada

Validate built features through conversational user acceptance testing.

Updated Jan 21, 2026

Search Tags:#quality assurance #conversational AI #software testing #feature validation #UAT

Ready to run

npx skills add https://github.com/zerAda/RestaurantAgentAutomation --skill gsd-verify-work-zerada

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gsd-verify-work
Source: https://github.com/zerAda/RestaurantAgentAutomation/tree/main/.agent/skills/gsd-verify-work
Command: npx skills add https://github.com/zerAda/RestaurantAgentAutomation --skill gsd-verify-work-zerada

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill allows for the validation of built features through conversational user acceptance testing (UAT), ensuring that the built features meet user expectations and work as intended.

Core Features & Use Cases

Conversational Testing: Validates features through direct, plain text conversations.
Persistent State: Keeps track of test sessions and results for accurate diagnosis.
Issue Diagnose and Plan: Automatically identifies issues and prepares fix plans.
Output Tracking: Generates a report in the format {phase_num}-UAT.md tracking all test results.

Quick Start

To initiate a feature validation test for phase 4, say "Validate features for phase 4".

Frequently Asked Questions about gsd-verify-work

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is conversational user acceptance testing for feature validation?▼

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.

How do I run a user acceptance test for a specific development phase?▼

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.

Does conversational UAT automatically diagnose issues and generate fix plans?▼

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.

Do I need persistent state management for software testing sessions?▼

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.

What is the best way to track UAT results for quality assurance?▼

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.