Which programming languages are supported?

While the core principles apply to all codebases, it includes specific technical patterns and tool configurations for JavaScript/TypeScript, Python, and Go.

What advanced techniques are included?

The skill covers high-level strategies such as Git bisect for regression tracking, differential debugging to compare environments, and trace debugging for complex execution flows.

Can this skill help with production-only bugs?

Yes, it includes specialized patterns for production debugging, focusing on safe evidence gathering, log analysis, and local reproduction using anonymized data.

How does this skill improve the debugging process?

It replaces trial-and-error with a scientific approach, providing structured phases for reproduction, hypothesis formation, and verification to ensure the root cause is addressed rather than just the symptoms.

Does it help with performance issues?

Absolutely. It provides guidance on using profilers, identifying N+1 queries, and detecting memory leaks using heap snapshots and performance marks.

Debugging Strategies & Root Cause Analysis

Name: Debugging Strategies & Root Cause Analysis
Author: HermeticOrmus

byHermeticOrmus

Security & Testing

Master systematic debugging techniques and profiling tools to efficiently resolve bugs and performance bottlenecks across any technology stack.

About

The Debugging Strategies skill transforms the often-frustrating process of bug hunting into a disciplined, scientific methodology. It equips Claude with structured frameworks for isolating issues, reproducing complex errors, and conducting deep root cause analysis using a variety of specialized tools for JavaScript, Python, and Go. By implementing methodical checklists and advanced techniques like binary search debugging, differential analysis, and memory leak detection, this skill ensures that developers can move beyond guesswork to provide stable, long-term fixes for even the most elusive production issues.

Key Features

Comprehensive checklists for reproduction, information gathering, and verification
0 GitHub stars
Scientific method framework for systematic bug isolation and resolution
Techniques for memory leak detection and performance bottleneck identification
Advanced patterns for resolving intermittent, flaky, and race-condition bugs
Language-specific profiling and debugging configurations for JS, Python, and Go

Use Cases

Investigating and resolving performance regressions in high-traffic environments
Establishing a systematic debugging workflow for unfamiliar or legacy codebases
Tracking down elusive memory leaks and race conditions in distributed systems

About

Key Features

Comprehensive checklists for reproduction, information gathering, and verification
0 GitHub stars
Scientific method framework for systematic bug isolation and resolution
Techniques for memory leak detection and performance bottleneck identification
Advanced patterns for resolving intermittent, flaky, and race-condition bugs
Language-specific profiling and debugging configurations for JS, Python, and Go

Use Cases

Investigating and resolving performance regressions in high-traffic environments
Establishing a systematic debugging workflow for unfamiliar or legacy codebases
Tracking down elusive memory leaks and race conditions in distributed systems