When should I use the Systematic Debugging skill?

Use it for any technical issue including test failures, production bugs, or unexpected behavior—especially when you feel tempted to use a 'quick fix' under time pressure.

What happens if a fix doesn't work after multiple attempts?

If three or more fixes fail, the skill identifies an architectural red flag. Instead of a fourth fix, it prompts a discussion about whether the underlying pattern or architecture is fundamentally sound.

What is the 'Iron Law' of this debugging skill?

The Iron Law dictates that no fixes can be proposed until Phase 1 (Root Cause Investigation) is complete. This ensures the underlying issue is understood rather than just masking symptoms.

How does the skill handle complex, multi-component systems?

It uses diagnostic instrumentation to log data at every component boundary (e.g., API to Database), allowing you to see exactly where the data flow breaks before attempting a fix.

Systematic Debugging

Name: Systematic Debugging
Author: otibo-repos

byotibo-repos

0•

Security & Testing

Implements a rigorous four-phase framework to identify root causes and resolve technical issues without introducing new bugs.

The Systematic Debugging skill transforms the troubleshooting process into a scientific methodology, moving away from guess-and-check patches toward deep root cause investigation. It guides the AI through four distinct phases—investigation, pattern analysis, hypothesis testing, and implementation—ensuring that every fix is backed by evidence and verified by a failing test case. This skill is essential for resolving complex regressions, multi-component failures, and architectural issues where surface-level symptoms often mask deeper logic flaws.

Key Features

01Evidence-based troubleshooting that prevents symptom-masking and technical debt

02Mandatory diagnostic instrumentation for tracing data across multi-component systems

030 GitHub stars

04Four-phase framework: Investigation, Analysis, Hypothesis, and Implementation

05Architectural review triggers that stop 'thrashing' after three failed fix attempts

06Integration with Test-Driven Development (TDD) to ensure fixes are verified

Use Cases

01Fixing recurring bugs where previous 'quick fixes' have failed to address the underlying problem

02Resolving elusive intermittent test failures in CI/CD pipelines through data flow tracing

03Debugging complex state issues in multi-layer applications like Minecraft server landing pages

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add otibo-repos/minecraft_landing_page debug

For use in Claude.ai and ChatGPT

Key Features

01Evidence-based troubleshooting that prevents symptom-masking and technical debt

02Mandatory diagnostic instrumentation for tracing data across multi-component systems

030 GitHub stars

04Four-phase framework: Investigation, Analysis, Hypothesis, and Implementation

05Architectural review triggers that stop 'thrashing' after three failed fix attempts

06Integration with Test-Driven Development (TDD) to ensure fixes are verified

Use Cases

01Fixing recurring bugs where previous 'quick fixes' have failed to address the underlying problem

02Resolving elusive intermittent test failures in CI/CD pipelines through data flow tracing

03Debugging complex state issues in multi-layer applications like Minecraft server landing pages