Does it include performance optimization?

Yes, it covers performance debugging through profiling, identifying N+1 queries, and analyzing memory usage to resolve bottlenecks.

Which programming languages are supported?

The skill provides specific patterns and tools for JavaScript, TypeScript, Python, and Go, though the general methodology is language-agnostic and applies to any codebase.

What tools are covered by this skill?

It guides the use of industry-standard debuggers like Chrome DevTools, PDB (Python), Delve (Go), as well as performance profiling tools and version control utilities like Git bisect.

How does this skill improve the debugging process?

It replaces trial-and-error with a systematic approach based on the scientific method, ensuring every bug is consistently reproduced, isolated, and verified before a fix is applied.

Can it help with production-only issues?

Yes, it includes specific patterns for gathering evidence from logs, error trackers, and environment differentials to reproduce production bugs safely in local or staging environments.

Debugging Strategies

Name: Debugging Strategies
Author: 3commas-io

by3commas-io

Security & Testing

Implements systematic debugging techniques and root cause analysis to resolve complex software defects and performance bottlenecks.

About

This skill equips Claude with a rigorous, methodology-driven approach to troubleshooting code across multiple languages including JavaScript, Python, and Go. It moves beyond guesswork by applying the scientific method—observation, hypothesis formation, and experimental verification—to isolate elusive bugs, analyze memory leaks, and optimize application performance. Whether you are dealing with flaky production issues, navigating unfamiliar codebases, or performing deep-dive profiling, this skill provides the structured frameworks and tool-specific patterns needed to identify and resolve root causes efficiently.

Key Features

0 GitHub stars
Systematic root cause analysis using the scientific method
Step-by-step checklists for reproducing and documenting elusive defects
Language-specific debugging configurations for Node.js, Python, and Go
Advanced troubleshooting techniques like binary search and differential analysis
Performance profiling and memory leak detection strategies

Use Cases

Resolving intermittent race conditions and flaky bugs in distributed systems
Identifying and fixing memory leaks or performance regressions in production environments
Isolating the source of a regression using Git bisect and differential debugging

About

Key Features

0 GitHub stars
Systematic root cause analysis using the scientific method
Step-by-step checklists for reproducing and documenting elusive defects
Language-specific debugging configurations for Node.js, Python, and Go
Advanced troubleshooting techniques like binary search and differential analysis
Performance profiling and memory leak detection strategies

Use Cases

Resolving intermittent race conditions and flaky bugs in distributed systems
Identifying and fixing memory leaks or performance regressions in production environments
Isolating the source of a regression using Git bisect and differential debugging