debug:scikit-learn

SKILL.md

This guide provides a systematic approach to debugging Scikit-learn machine learning code. Follow these phases to identify and resolve issues efficiently.

Debug Scikit-learn issues systematically. Use when encountering model errors like NotFittedError, shape mismatches between train and test data, NaN/infinity value errors, pipeline configuration issues, convergence warnings from optimizers, cross-validation failures due to class imbalance, data leakage causing suspiciously high scores, or preprocessing errors with ColumnTransformer and feature alignment. Source: snakeo/claude-debug-and-refactor-skills-plugin.

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/snakeo/claude-debug-and-refactor-skills-plugin --skill debug:scikit-learn Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

Security certified for safe and reliable code One-click installation with simplified configuration Compatible with Claude Code, Cursor, and more

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