Can it help find performance bottlenecks?

Yes, it includes techniques for performance profiling and identifies common culprits like N+1 queries, unnecessary re-renders, and synchronous I/O issues.

What languages does this skill support?

It includes specific patterns and configurations for JavaScript, TypeScript, Python, and Go, though the general systematic principles apply to any technology stack.

What is 'Rubber Duck Debugging' in this context?

It is a strategy included in the skill's mindset section that involves explaining the code and problem out loud to reveal logical gaps and hidden assumptions.

How does this help with production bugs?

It provides a framework for gathering evidence from error trackers and logs to reproduce issues locally using safe investigation techniques without compromising the production environment.

Debugging Strategies

Name: Debugging Strategies
Author: HermeticOrmus

byHermeticOrmus

Security & Testing

Implements systematic debugging workflows, profiling techniques, and root cause analysis to resolve complex software issues across any technology stack.

About

The Debugging Strategies skill transforms the often-frustrating process of troubleshooting into a methodical, data-driven practice. By leveraging the scientific method, the skill helps developers move beyond guesswork to consistently reproduce, isolate, and fix elusive bugs. It provides comprehensive patterns for JavaScript, Python, and Go, covering everything from basic console logging and breakpoints to advanced memory leak detection, performance profiling, and git bisect workflows. Whether dealing with intermittent race conditions in development or critical failures in production, this skill offers the frameworks needed to identify root causes quickly and implement long-term fixes.

Key Features

Advanced troubleshooting techniques including Binary Search and Differential Debugging.
Language-specific debugger configurations for JavaScript, Python, and Go environments.
0 GitHub stars
Systematic four-phase debugging process: Reproduce, Gather, Hypothesize, and Verify.
Specialized strategies for resolving intermittent race conditions and production-only failures.
Comprehensive memory leak detection and performance profiling patterns.

Use Cases

Troubleshooting intermittent race conditions or 'flaky' bugs in complex distributed systems.
Locating the specific commit that introduced a regression using automated Git bisect workflows.
Identifying and resolving memory leaks or performance bottlenecks in high-load applications.

About

Key Features

Advanced troubleshooting techniques including Binary Search and Differential Debugging.
Language-specific debugger configurations for JavaScript, Python, and Go environments.
0 GitHub stars
Systematic four-phase debugging process: Reproduce, Gather, Hypothesize, and Verify.
Specialized strategies for resolving intermittent race conditions and production-only failures.
Comprehensive memory leak detection and performance profiling patterns.

Use Cases

Troubleshooting intermittent race conditions or 'flaky' bugs in complex distributed systems.
Locating the specific commit that introduced a regression using automated Git bisect workflows.
Identifying and resolving memory leaks or performance bottlenecks in high-load applications.