Can this skill help find when a bug was first introduced?

Absolutely. It includes a workflow for Technique 1: Binary Search Debugging using Git bisect to automatically narrow down the specific commit that introduced a regression.

How does this skill help with 'it works on my machine' issues?

It provides a structured 'Differential Debugging' framework to systematically compare working and broken environments, helping you isolate differences in OS versions, dependencies, and environment variables.

What is the 'Scientific Method' in debugging?

It is a 5-step iterative process: Observe actual behavior, Hypothesize the cause, Experiment to test the theory, Analyze results, and Repeat until the root cause is definitively identified.

Does it include specific tools for different programming languages?

Yes, it includes specialized configurations and code snippets for Chrome DevTools, VS Code launch configurations, Python's pdb/ipdb, and Go's Delve debugger and pprof tools.

Debugging Strategies & Root Cause Analysis

Name: Debugging Strategies & Root Cause Analysis
Author: yusoofsh

byyusoofsh

보안 및 테스팅

Transforms troubleshooting into a systematic scientific process for identifying, isolating, and fixing complex bugs across any technology stack.

소개

The Debugging Strategies skill provides a comprehensive framework to move beyond guesswork and into methodical problem-solving. It equips Claude with the scientific method for debugging, reproduction checklists, and language-specific workflows for JavaScript, Python, and Go. From identifying memory leaks and race conditions to using advanced techniques like Git bisect and differential debugging, this skill ensures that even the most elusive production issues are tracked down and resolved at their root cause rather than just treating symptoms.

주요 기능

Detailed reproduction and information-gathering checklists
0 GitHub stars
Scientific method implementation for systematic hypothesis testing
Language-specific debugger configurations (JS, Python, Go)
Specialized patterns for intermittent, performance, and production bugs
Advanced binary search and differential debugging techniques

사용 사례

Conducting root cause analysis on legacy or unfamiliar codebases
Isolating and fixing elusive race conditions in distributed systems
Identifying and resolving memory leaks and performance bottlenecks

소개

주요 기능

Detailed reproduction and information-gathering checklists
0 GitHub stars
Scientific method implementation for systematic hypothesis testing
Language-specific debugger configurations (JS, Python, Go)
Specialized patterns for intermittent, performance, and production bugs
Advanced binary search and differential debugging techniques

사용 사례

Conducting root cause analysis on legacy or unfamiliar codebases
Isolating and fixing elusive race conditions in distributed systems
Identifying and resolving memory leaks and performance bottlenecks