troubleshooting

Diagnose and resolve failures using a structured troubleshooting workflow.

34|7|Updated Nov 29, 2025
One-click install
npx skills add https://github.com/jkitchin/skillz --skill troubleshooting-jkitchin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: troubleshooting
Source: https://github.com/jkitchin/skillz/tree/main/skills/technical/troubleshooting
Command: npx skills add https://github.com/jkitchin/skillz --skill troubleshooting-jkitchin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, numpy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Systematic troubleshooting guidance for diagnosing and resolving errors, performance issues, and failures across domains.

Core Features & Use Cases

  • Universal Methodology: Understand → Gather → Hypothesize → Test → Verify → Document.
  • Frameworks: 5 Whys, Fishbone, Binary Search, hypothesis-driven debugging.
  • Output: actionable fixes, verification steps, and documentation templates.

Quick Start

Use the five-step universal workflow to diagnose an unexpected failure, logging hypotheses and results.

Frequently Asked Questions about troubleshooting

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

FAQPage Schema
How do I systematically debug code when I don't know where the problem is?

Use structured troubleshooting methodology: understand the failure, gather relevant data, form hypotheses, test them systematically, verify the fix, and document results. Binary search and hypothesis-driven debugging narrow down root causes efficiently across software, systems, and configurations.

What's the difference between the 5 Whys, Fishbone, and binary search for problem solving?

5 Whys traces causal chains by asking why repeatedly; Fishbone maps contributing factors across categories; binary search isolates failures by systematically eliminating half the variables. Choose based on problem type: causal chains, multi-factor failures, or reproducible narrowing.

How do I create a reproduction case for intermittent or hard-to-diagnose failures?

Gather logs and environmental data, form hypotheses about trigger conditions, test systematically to isolate variables, and document the consistent steps that recreate the issue. This workflow applies to configuration problems, outages, and performance degradation.

Can I use this troubleshooting approach for system outages and performance issues, not just code bugs?

Yes. The universal methodology—understand, gather, hypothesize, test, verify, document—works across software debugging, diagnosing outages, resolving configuration issues, and investigating intermittent behavior in any domain.

What information do I need to gather before starting hypothesis testing?

Collect logs, error messages, environmental context, recent changes, and reproducibility details. Information gathering feeds hypothesis generation; structured log analysis and domain-specific patterns guide which variables to test first.