systematic-debugging

Diagnose software bugs through evidence-based root cause analysis.

1|1|Updated Feb 5, 2026

Search Tags:#debugging #verification #traceability #hypothesis #reproducibility #root-cause #evidence-based

Ready to run

npx skills add https://github.com/ChooJeongHo/MovieFinder --skill systematic-debugging-choojeongho

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/ChooJeongHo/MovieFinder/tree/main/.claude/skills/systematic-debugging
Command: npx skills add https://github.com/ChooJeongHo/MovieFinder --skill systematic-debugging-choojeongho

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematically diagnose and fix software bugs using evidence-driven root cause analysis. No guessing — follow the evidence.

Core Features & Use Cases

Collects and classifies evidence, estimates root causes, and documents traceable fixes.
Supports phase-based debugging workflows from reproduction to verification.
Scales across frontend and backend systems, teams, and CI pipelines.

Quick Start

Reproduce the bug, collect evidence, form hypotheses, and document a minimal fix with verification steps.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema

How do I debug software bugs systematically instead of guessing?▼

Systematic debugging requires structured evidence collection to estimate root causes, form prioritized hypotheses, and document traceable fixes. You reproduce the bug, classify evidence, test hypotheses iteratively, and verify minimal fixes without guessing.

What is evidence-based root cause analysis in debugging?▼

Evidence-based root cause analysis is a debugging method that replaces speculation with structured verification. It involves collecting traceable evidence, prioritizing hypotheses by likelihood, and iteratively testing fixes until the verified root cause is documented.

How do I ensure reproducibility when fixing bugs across frontend and backend codebases?▼

Reproducibility is ensured by following phase-based workflows from initial reproduction to final verification. Collect structured evidence across frontend and backend systems, document each hypothesis test, and verify minimal fixes with reproducible steps.

Does systematic debugging work for both frontend and backend systems?▼

Yes, systematic debugging scales across frontend and backend codebases, teams, and CI pipelines. The evidence-driven workflow applies consistently to reproduction, classification, hypothesis testing, and iterative fixes regardless of system type.

What's the best way to document a traceable root cause fix?▼

The best way to document a traceable fix is to record structured evidence, prioritized hypotheses, and reproducible verification steps. Maintain traceability from initial bug reproduction through classification to the minimal iterative fix applied.

When should I use hypothesis testing instead of trial-and-error debugging?▼

Use hypothesis testing when bugs require reproducible verification and traceable documentation. It prioritizes root causes by evidence, ensuring minimal fixes are validated iteratively rather than relying on unstructured trial-and-error code changes.