Does it actually fix the code for me?

It guides a methodical investigative process to identify the true root cause first, then develops and verifies a minimal solution based on the evidence gathered.

When should I use the Debug Like Expert skill?

Use it for complex, persistent bugs that have resisted standard troubleshooting or when you need a rigorous, documented root cause analysis for critical systems.

What tools does this skill use during an investigation?

It leverages MCP servers for documentation, web searches for error patterns, and rigorous file reading to ensure a complete understanding of the system architecture.

Why does the skill emphasize skepticism toward my own code?

It is designed to counter confirmation bias, where developers assume their logic works as intended, which often blinds them to implementation errors in their own designs.

How does this skill handle different programming languages?

The skill includes a context scanner that automatically detects your project type—such as Python, JavaScript, Rust, or Swift—and loads domain-specific debugging expertise.

Debug Expert Mode

Name: Debug Expert Mode
Author: glittercowboy

byglittercowboy

•

770

Security & Testing

Activates a methodical, scientific debugging protocol to solve complex software bugs through evidence gathering and hypothesis testing.

About

This skill transforms Claude into a senior-level debugging consultant, replacing quick fixes with a rigorous investigative framework. It automatically detects your project's domain—such as React, Swift, or Rust—to load specialized expertise and enforces a strict protocol of evidence collection, falsifiable hypothesis testing, and systematic verification. It is specifically designed to overcome cognitive biases that developers face when debugging their own code, ensuring that every solution is backed by empirical proof and doesn't introduce regressions.

Key Features

Comprehensive system mapping and trace execution analysis
Standardized output format for professional debugging reports
Cognitive bias mitigation for more objective code analysis
Scientific investigation protocol using hypothesis-driven testing
770 GitHub stars
Automated domain detection to load specialized project context

Use Cases

Performing root cause analysis for production bugs where behavior contradicts code assumptions
Systematic verification of mission-critical fixes to ensure zero regressions
Resolving intermittent race conditions or complex logic errors that standard troubleshooting fails to catch

About

Key Features

Comprehensive system mapping and trace execution analysis
Standardized output format for professional debugging reports
Cognitive bias mitigation for more objective code analysis
Scientific investigation protocol using hypothesis-driven testing
770 GitHub stars
Automated domain detection to load specialized project context

Use Cases

Performing root cause analysis for production bugs where behavior contradicts code assumptions
Systematic verification of mission-critical fixes to ensure zero regressions
Resolving intermittent race conditions or complex logic errors that standard troubleshooting fails to catch