systematic-debugging

Identify root causes of bugs before applying fixes in multi-component systems.

1|Updated Feb 24, 2026

Search Tags:#debugging #troubleshooting #systematic #diagnostics #phases #root-cause

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npx skills add https://github.com/dzackgarza/ai --skill systematic-debugging-dzackgarza

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/dzackgarza/ai/tree/main/opencode/skills/systematic-debugging
Command: npx skills add https://github.com/dzackgarza/ai --skill systematic-debugging-dzackgarza

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematic debugging provides a disciplined, repeatable approach to diagnosing issues by prioritizing root-cause investigation over quick, symptom-focused fixes.

Core Features & Use Cases

Phase-driven workflow with four phases: Root Cause Investigation, Pattern Analysis, Hypothesis and Testing, and Implementation.
Emphasizes evidence gathering, reproducibility, data-flow tracing, and incremental fixes across multi-component systems.
Use cases include resolving test failures, production bugs, performance problems, and integration issues where reliable root-cause determination is essential.

Quick Start

Describe the issue in detail, reproduce it consistently, and gather evidence to identify the root cause before proposing any fix.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema

What is systematic debugging and when should I use it for troubleshooting?▼

Systematic debugging is a disciplined approach to troubleshooting that prioritizes root-cause investigation over symptom-based patches. You should use it to resolve test failures, production bugs, and integration issues across multi-component systems.

How do I find the root cause of a bug before applying a fix?▼

To find the root cause of a bug, follow a four-phase workflow: Root Cause Investigation, Pattern Analysis, Hypothesis and Testing, and Implementation. You must gather evidence, trace data flows, and consistently reproduce the issue before proposing any fix.

Does this debugging method work for production environments and multi-component systems?▼

Yes, this debugging method works across test, staging, and production environments. It is specifically designed for multi-component systems, enforcing evidence collection, reproducibility, and safe, incremental changes to ensure reliable root-cause determination.

What's the best way to stop guessing and fix recurring software bugs?▼

The best way to stop guessing and fix recurring software bugs is to enforce pattern analysis and evidence gathering. By demanding reproducibility and data-flow tracing before implementation, you prevent symptom-focused patches and eliminate guesswork.

What are the limitations of using a phase-driven debugging workflow?▼

The limitation of a phase-driven debugging workflow is the required upfront investment to reproduce issues consistently and gather evidence. You should not use this approach if you need immediate, unverified patches and cannot safely apply incremental changes.