Why does this skill prevent proposing fixes immediately?

Quick patches often mask underlying issues and lead to code thrashing. This skill ensures that the root cause is fully understood first, leading to permanent fixes and fewer regressions.

How does it handle multi-component systems?

It uses diagnostic instrumentation at component boundaries to log data entry and exit, verifying environment propagation to pinpoint exactly which layer is failing.

What happens if three or more fix attempts fail?

The skill identifies this as a potential architectural issue rather than a simple bug, prompting a fundamental design discussion instead of continuing with ineffective patches.

Does this skill work with Test-Driven Development (TDD)?

Yes, Phase 4 of the process requires creating a failing test case before implementing any fix, ensuring the bug is reproducible and remains fixed in the future.

Systematic Debugging

Name: Systematic Debugging
Author: LyQing63

byLyQing63

0•

セキュリティとテスト

Implements a rigorous, four-phase methodology to identify root causes and ensure reliable fixes for complex technical issues.

This skill transforms Claude's debugging process from a guess-and-check approach into a scientific, evidence-based workflow. It enforces a strict 'Iron Law' where no fixes are proposed until a complete root cause investigation is performed. By guiding the AI through investigation, pattern analysis, hypothesis testing, and implementation, it prevents shallow symptom fixes, reduces the introduction of new bugs, and signals when architectural problems require human intervention rather than more patches. It is particularly effective for multi-component systems, intermittent failures, and deep-seated data flow issues.

主な機能

01Scientific hypothesis testing with minimal, single-variable verification

02Automatic escalation to architectural review after three failed fix attempts

03Strict 'No Fixes Without Root Cause' enforcement to prevent thrashing

040 GitHub stars

05Multi-layer diagnostic instrumentation for troubleshooting complex systems

06Deep data flow tracing to locate original triggers in call stacks

ユースケース

01Investigating deep data flow issues and unexpected behavior in unfamiliar codebases

02Debugging intermittent test failures or production bugs in distributed systems

03Resolving recurring issues where previous 'quick fixes' have failed to stick

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lyqing63/lyqing.opencode systematic-debugging

For use in Claude.ai and ChatGPT

Download Skill