diagnose-issues

Ugh. Yet another repetitive task, automated perfectly.

Updated Nov 16, 2025

Search Tags:#automation #planning #debug #parallel #diagnose #root-cause #uat

Ready to run

npx skills add https://github.com/RayOfSteel-DHBW/TeilAutoNeu --skill diagnose-issues-rayofsteel-dhbw

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: diagnose-issues
Source: https://github.com/RayOfSteel-DHBW/TeilAutoNeu/tree/main/.github/skills/diagnose-issues
Command: npx skills add https://github.com/RayOfSteel-DHBW/TeilAutoNeu --skill diagnose-issues-rayofsteel-dhbw

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrate parallel debug agents to investigate UAT gaps and find root causes. Spawns debug agents per gap, collects diagnoses, updates UAT.md.

Core Features & Use Cases

Diagnoses: orchestrates parallel agents to surface root causes for each UAT gap; collects evidence and artifacts to inform fixes.
Automation: updates UAT.md with root causes, artifacts, and missing steps; handoffs to plan-phase.
Use Case: In a UAT run with multiple gaps, spawn one agent per gap to discover causes in parallel and accelerate remediation.

Quick Start

Spawn parallel debug agents for each identified UAT gap and begin autonomous diagnosis.

Frequently Asked Questions about diagnose-issues

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

FAQPage Schema

How do I find the root cause of multiple UAT gaps at the same time?▼

To find the root cause of multiple UAT gaps concurrently, you can orchestrate parallel debug agents that each investigate a single gap. This approach aggregates root causes and artifacts concurrently to accelerate remediation.

How do I automate updating UAT.md with identified root causes and artifacts?▼

Automating UAT.md updates involves parsing identified gaps, spawning debug agents to collect evidence, and automatically writing the discovered root causes, artifacts, and missing steps back into the UAT.md file for planning.

What is the best way to diagnose UAT gaps in a QA environment?▼

The best way to diagnose UAT gaps in a QA environment is to spawn parallel debug agents that autonomously investigate each gap, surface root causes, and collect evidence to inform fixes before handing off to the plan phase.

Can I use parallel debug agents for diagnosing issues in production-like UATs?▼

Yes, you can apply parallel debug agents to production-like UATs. The workflow coordinates multiple agents to investigate identified gaps concurrently, aggregating diagnoses and artifacts for subsequent planning.

Do I need an existing UAT.md file to start diagnosing UAT issues?▼

Yes, you need an existing UAT.md file. The workflow parses identified gaps from UAT.md to spawn individual debug agents, and later updates the same file with the collected root causes and artifacts.