debug-like-expert

The 'debug-like-expert' skill is designed to assist with deep, systematic debugging of complex issues by activating a methodical investigation protocol. This skill focuses on evidence gathering, hypothesis testing, and rigorous verification, and it is intended for use when standard troubleshooting methods have failed or when issues require a more thorough root cause analysis. By encouraging the user to scrutinize code more critically, particularly their own code, it helps uncover potential errors that could be overlooked due to cognitive biases. The skill follows a scientific method approach, ensuring each problem is dissected thoroughly rather than relying on quick fixes.

Main features include the ability to scan the project directory for relevant files, detect domain-specific expertise, and load the appropriate debugging protocols for various programming environments. The skill is highly flexible, as it works both with domain-specific expertise (e.g., Python, Swift, Rust) or with general debugging techniques when no domain knowledge is found. Additionally, it incorporates inference rules to automatically detect the domain from the user's description or codebase and prompt the user to load the corresponding expertise. In the absence of a domain match, it presents the user with options to either continue with general debugging or select a domain to load.

This skill is ideal for developers, software engineers, and technical troubleshooters working on complex codebases across various languages and environments. It is particularly useful when dealing with hard-to-diagnose issues or when debugging involves multiple layers of complexity, such as performance bottlenecks or subtle implementation bugs. Users who are already familiar with scientific debugging methods or those working in teams tackling intricate system issues will benefit most from this tool.