Does it integrate with testing frameworks?

Absolutely. Phase 4 requires the creation of a failing test case before any fix is implemented, ensuring the solution is verified and reproducible.

Why can't I just apply a quick fix with this skill?

Quick fixes often mask underlying issues and lead to regressions. This skill enforces the 'Iron Law' of finding the root cause first to ensure the problem is solved permanently.

Does this skill help with distributed systems?

Yes, it includes specific evidence-gathering steps for systems with multiple boundaries, such as CI/CD pipelines, APIs, and database layers.

What happens if multiple fix attempts fail?

If three attempts fail, the skill mandates an architectural review. This helps identify if the issue is a fundamental design flaw rather than a simple coding error.

When is the best time to use the Systematic Debugging skill?

Use it for any technical issue, especially when under time pressure, when a 'quick fix' has already failed, or when dealing with complex multi-component systems.

Systematic Debugging

Name: Systematic Debugging
Author: saar120

bysaar120

0•

安全与测试

Implements a disciplined, four-phase debugging methodology to identify root causes and eliminate bug-fixing guesswork.

This skill enforces a rigorous debugging framework for Claude Code, prioritizing deep root cause analysis over superficial patches. It guides the AI through four mandatory phases: investigative evidence gathering, pattern analysis against working examples, scientific hypothesis testing, and controlled implementation with failing test cases. By preventing 'guess-and-check' behavior and identifying architectural flaws after multiple failed attempts, this skill ensures more stable resolutions and significantly reduces the technical debt caused by symptom-level fixes.

主要功能

010 GitHub stars

02Architectural pivot detection triggered after three failed fix attempts

03Evidence-gathering protocols for multi-component systems and distributed architectures

04Automated requirement for failing test cases to verify permanent resolutions

05Root cause tracing techniques to track errors backward through the call stack

06Mandatory four-phase debugging lifecycle (Investigation, Pattern, Hypothesis, Implementation)

使用场景

01Investigating intermittent issues in complex, multi-layer systems or microservices

02Resolving persistent test failures or production bugs that resist standard troubleshooting

03Preventing 'band-aid' patches in high-stakes codebases where stability is critical

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add saar120/skillgate-registry systematic-debugging

For use in Claude.ai and ChatGPT

主要功能

010 GitHub stars

02Architectural pivot detection triggered after three failed fix attempts

03Evidence-gathering protocols for multi-component systems and distributed architectures

04Automated requirement for failing test cases to verify permanent resolutions

05Root cause tracing techniques to track errors backward through the call stack

06Mandatory four-phase debugging lifecycle (Investigation, Pattern, Hypothesis, Implementation)

使用场景

01Investigating intermittent issues in complex, multi-layer systems or microservices

02Resolving persistent test failures or production bugs that resist standard troubleshooting

03Preventing 'band-aid' patches in high-stakes codebases where stability is critical

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add saar120/skillgate-registry systematic-debugging

For use in Claude.ai and ChatGPT