systematic-debugging

Name: systematic-debugging
Availability: InStock
Author: goodworkrinkz

Enforce a four-phase root-cause analysis workflow before applying fixes.

Updated Mar 23, 2026

Search Tags:#debugging #software-engineering #reproduction #systematic-troubleshooting #root-cause-analysis #error-messages #evidence-gathering

Ready to run

npx skills add https://github.com/GOODWORKRINKZ/mylamp --skill systematic-debugging-goodworkrinkz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: systematic-debugging
Source: https://github.com/GOODWORKRINKZ/mylamp/tree/main/.agents/skills/systematic-debugging
Command: npx skills add https://github.com/GOODWORKRINKZ/mylamp --skill systematic-debugging-goodworkrinkz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams avoid guesswork by enforcing a systematic root-cause investigation before applying fixes, reducing wasted time on symptoms.

Core Features & Use Cases

Phase-based approach guiding teams through root-cause investigation, pattern analysis, hypothesis testing, and implementation.
Clear diagnostic workflow for issues across development, test, and production environments.
Use Case: when a bug appears in CI or production, follow the four phases to identify the true trigger and prevent regressions.

Quick Start

Follow the four-phase process to identify and document the root cause before implementing a fix.

Frequently Asked Questions about systematic-debugging

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

FAQPage Schema

How do I find the root cause of a production bug instead of just patching symptoms?▼

To find the root cause of a production bug, you need a systematic debugging workflow that enforces evidence gathering and trace data analysis before applying fixes. This approach uses a four-phase process to investigate the true trigger and prevent future regressions.

What is the best way to systematically troubleshoot failing integration tests and CI errors?▼

Systematic troubleshooting of integration test failures requires moving through root cause investigation, pattern analysis, hypothesis testing, and implementation. By gathering structured diagnostic evidence first, you can identify the actual trigger across development and test environments rather than guessing.

How do I debug performance problems using a hypothesis testing approach?▼

Debugging performance problems with hypothesis testing involves formulating potential explanations based on trace data and pattern analysis, then verifying those hypotheses before implementation. This ensures your performance fixes target the verified root cause with minimal changes.

Can I use a systematic root-cause analysis workflow for both development and production environments?▼

Yes, systematic root-cause analysis workflows apply to any technical issue across development, test, and production environments. The diagnostic process remains the same: gather evidence, analyze patterns, test hypotheses, and implement minimal-change fixes with verification.

Why should I gather evidence before applying a fix to a software bug?▼

Gathering evidence before applying a fix prevents wasted time on symptoms and avoids introducing regressions. Enforcing a structured investigation phase ensures you understand the error messages and trace data, leading to a minimal-change fix that resolves the true root cause.