investigate

Debug software errors through systematic root cause analysis phases.

Updated Jul 29, 2026
One-click install
npx skills add https://github.com/KrismithReddy12/gstack --skill investigate-krismithreddy12
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: investigate
Source: https://github.com/KrismithReddy12/gstack/tree/main/investigate
Command: npx skills add https://github.com/KrismithReddy12/gstack --skill investigate-krismithreddy12

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill provides a structured, repeatable framework for debugging software, ensuring that you identify the root cause of an issue before attempting a fix, which prevents "band-aid" solutions.

Core Features & Use Cases

  • Root Cause Analysis: Guides the AI through a four-phase process: investigate, analyze, hypothesize, and implement.
  • Proactive Debugging: Automatically triggers when errors, stack traces, or unexpected behaviors are reported.
  • Context Awareness: Integrates with project-specific learnings and prior investigations to avoid repeating past mistakes.

Quick Start

Invoke the investigate skill to perform a root cause analysis on the recent 500 error reported in the production logs.

Frequently Asked Questions about investigate

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

FAQPage Schema
What is systematic root cause analysis for debugging software errors?

Systematic root cause analysis is a structured debugging framework that identifies the fundamental cause of software errors before attempting fixes. It operates across investigation, analysis, hypothesis, and implementation phases to prevent temporary band-aid solutions and ensure durable code fixes.

How do I troubleshoot unexpected system behaviors using a structured debugging process?

You troubleshoot unexpected behaviors by triggering an automated investigation process that analyzes stack traces and integrates local project history. The process guides you through four phases: investigating symptoms, analyzing data, forming hypotheses, and implementing a verified fix.

Can I use project history and telemetry for context-aware troubleshooting?

Yes, context-aware troubleshooting integrates directly with project-specific learnings, telemetry, and prior investigations. This pattern recognition capability helps avoid repeating past mistakes by applying historical debugging context to current error analysis.

Does automated error handling work for production environment stack traces?

Automated error handling proactively triggers when stack traces or unexpected behaviors are reported in production logs. It performs root cause analysis on the errors by leveraging integrated telemetry and project history to deliver context-aware debugging.

What's the best way to stop applying band-aid fixes to recurring software bugs?

The best way to stop applying band-aid fixes is to enforce a repeatable debugging framework that requires root cause identification before implementation. This structured approach analyzes underlying issues across four phases, ensuring the applied code fixes are durable.