Advanced Debugging Strategies

About

This skill transforms the debugging process from disorganized guesswork into a structured, scientific workflow. It guides Claude to meticulously reproduce bugs, gather environmental data, form testable hypotheses, and utilize language-specific diagnostic tools for JavaScript, Python, and Go. Whether tackling elusive race conditions, memory leaks, or production performance bottlenecks, the skill provides a comprehensive framework for root cause analysis, differential debugging, and verified fixes to ensure long-term codebase stability.

Key Features

• Memory leak detection and performance bottleneck identification
• Implementation of the five-step scientific debugging method
• 0 GitHub stars
• Language-specific profiling and debugger configurations for JS, Python, and Go
• Specialized strategies for intermittent, flaky, and production-only bugs
• Advanced binary search debugging using Git bisect and differential analysis

Use Cases

• Performing root cause analysis on production crashes using stack traces and logs
• Identifying and fixing memory leaks or CPU bottlenecks in high-scale applications
• Isolating non-deterministic 'flaky' bugs in distributed systems or async code