debugging

Diagnose software bugs through evidence collection and hypothesis testing.

187|20|Updated Nov 20, 2025

Search Tags:#debugging #troubleshooting #observability #diagnostics #root-cause #reproduction

Ready to run

npx skills add https://github.com/TheBushidoCollective/han --skill debugging-thebushidocollective

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: debugging
Source: https://github.com/TheBushidoCollective/han/tree/main/core/skills/debugging
Command: npx skills add https://github.com/TheBushidoCollective/han --skill debugging-thebushidocollective

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a disciplined, repeatable approach to investigating bugs, helping you uncover root causes quickly and with less guesswork.

Core Features & Use Cases

Observe & Collect Evidence: Gather symptoms, logs, errors, and environment details to frame the investigation.
Hypothesis-Driven Diagnosis: Form and test hypotheses across categories like logic, state, async issues, and environment.
Structured Experimentation: Design tests with clear success criteria and document outcomes to guide fixes.

Quick Start

Use the debugging skill when a feature misbehaves: start by listing the symptom, reproduce steps, and collect logs to form your first hypothesis.

Frequently Asked Questions about debugging

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

FAQPage Schema

How do I systematically diagnose a bug to find its root cause?▼

Debugging systematically involves collecting evidence like logs and stack traces, forming testable hypotheses about logic or state issues, running structured experiments with clear success criteria, and documenting outcomes. This disciplined approach uncovers root causes faster than guesswork, applying across web, mobile, and backend applications.

What information should I gather when troubleshooting an application error?▼

Gather symptoms, reproduction steps, logs, stack traces, and environment details. Structured evidence collection frames your investigation and enables hypothesis generation. Document what you observe before forming theories about what went wrong.

How do I create a reproducible test case for a bug?▼

Design experiments with clear success criteria and document outcomes. Include precise reproduction steps, the exact conditions under which the bug appears, and measurable ways to verify whether your hypothesis fixes it. Reproducibility guides both diagnosis and validation.

Can debugging skills apply to web, mobile, and backend systems?▼

Yes. This disciplined diagnostic approach handles symptom collection, hypothesis testing, and root-cause analysis across web, mobile, and backend applications. The methodology adapts to different platforms while maintaining structured evidence gathering and experimental validation.

What's the difference between observability and debugging?▼

Observability provides the visibility into system behavior through logs, metrics, and traces. Debugging uses that observability data—along with hypothesis-driven experimentation—to investigate specific failures and identify root causes in your application.

When should I use a hypothesis-driven approach instead of trial-and-error fixes?▼

Use hypothesis-driven debugging when you need reliable root-cause analysis and faster resolution. Forming testable theories about logic, state, async, or environment issues prevents wasted effort and produces documented remediation plans, not temporary patches.