investigate

Diagnose software failures through a four-phase root-cause investigation workflow.

Updated Mar 14, 2026

Search Tags:#analysis #debug #grep #investigate #root-cause #reproduction #stack-trace

Ready to run

npx skills add https://github.com/Bradliebs/VolumeTurtle --skill investigate-bradliebs

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: investigate
Source: https://github.com/Bradliebs/VolumeTurtle/tree/main/.gstack/investigate
Command: npx skills add https://github.com/Bradliebs/VolumeTurtle --skill investigate-bradliebs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging with root-cause investigation to identify underlying issues rather than patching symptoms.

Core Features & Use Cases

Four-phase workflow: investigate, analyze, hypothesize, implement to guide problem solving.
Iron Law: no fixes without root cause evidence, ensuring durable resolutions.
Proactive invocation: can be triggered when users report errors or broken behavior to steer debugging.
Evidence gathering: uses Grep, Read, and WebSearch to collect traces, logs, and contextual data.

Quick Start

Describe the bug to start the root-cause investigation and let the skill guide the four phases to surface the real fix.

Frequently Asked Questions about investigate

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

FAQPage Schema

What is root-cause debugging and how does it fix software failures?▼

Root-cause debugging identifies the underlying source of software failures using evidence like stack traces and logs, ensuring durable resolutions rather than temporarily patching symptoms.

How do I debug a stack trace to find the actual error?▼

Debug a stack trace through a four-phase workflow: investigate, analyze, hypothesize, and implement. Gather contextual data using Grep, Read, and WebSearch to surface the verified root cause.

What is the best way to investigate unexpected application behavior across deployments?▼

Investigate unexpected behavior by gathering evidence from code, configurations, and deployments, enforcing an Iron Law that requires verified root cause evidence before applying any fixes.

Can I use this systematic debugging approach for errors in configurations and code?▼

Yes, systematic debugging applies to errors and unexpected behavior across code, configurations, and deployments, guiding you through investigation phases to implement fixes based on verified evidence.

Why should I avoid patching symptoms during root-cause analysis?▼

Avoid patching symptoms because the Iron Law of root-cause analysis mandates that no fixes be applied without verified root cause evidence, ensuring the underlying issue is durably resolved.