Can it help find performance bottlenecks?

Yes, it includes detailed guidance for using profiling tools like Chrome DevTools, Python's cProfile, and Go's pprof to identify N+1 queries and slow logic.

How does this help with production bugs?

It provides a structured workflow for gathering evidence via logs and error tracking, reproducing issues safely, and implementing fixes without disrupting live environments.

How does it handle 'flaky' or intermittent bugs?

The skill offers specific patterns for investigating race conditions, timing dependencies, and async execution order to force consistent reproduction of intermittent issues.

What languages does this skill support?

It provides specific strategies for JavaScript, TypeScript, Python, and Go, though the core systematic principles apply to any programming language or technology stack.

Advanced Debugging Strategies

Name: Advanced Debugging Strategies
Author: HermeticOrmus

byHermeticOrmus

セキュリティとテスト

Implements systematic debugging techniques and profiling tools to identify and resolve complex software bugs across any technology stack.

概要

This skill transforms the debugging process from frustrating guesswork into a methodical science by providing Claude with frameworks for reproduction, hypothesis testing, and tool-specific execution. It covers everything from memory leak detection and performance profiling in Python, Go, and TypeScript to advanced version control techniques like git bisect, making it an essential companion for developers tackling elusive production issues, race conditions, or unfamiliar codebases.

主な機能

Version control strategies including Git bisect for regression tracking
Systematic root cause analysis using the scientific method framework
Specialized workflows for intermittent (flaky) and production-level bugs
Language-specific debugging patterns for JavaScript, Python, and Go
0 GitHub stars
Advanced performance profiling and memory leak detection guides

ユースケース

Isolating the source of regressions in large codebases using binary search techniques
Tracking down intermittent race conditions or 'flaky' bugs in distributed systems
Identifying memory leaks and performance bottlenecks in high-scale applications

概要

主な機能

Version control strategies including Git bisect for regression tracking
Systematic root cause analysis using the scientific method framework
Specialized workflows for intermittent (flaky) and production-level bugs
Language-specific debugging patterns for JavaScript, Python, and Go
0 GitHub stars
Advanced performance profiling and memory leak detection guides

ユースケース

Isolating the source of regressions in large codebases using binary search techniques
Tracking down intermittent race conditions or 'flaky' bugs in distributed systems
Identifying memory leaks and performance bottlenecks in high-scale applications