model evaluator

SKILL.md

The Model Evaluator skill helps you rigorously assess and compare machine learning model performance across multiple dimensions. It guides you through selecting appropriate metrics, designing evaluation protocols, avoiding common statistical pitfalls, and making data-driven decisions about model selection.

Proper model evaluation goes beyond accuracy scores. This skill covers evaluation across the full spectrum: predictive performance, computational efficiency, robustness, fairness, calibration, and production readiness. It helps you answer not just "which model is best?" but "which model is best for my specific use case and constraints?"

Whether you are comparing LLMs, classifiers, or custom models, this skill ensures your evaluation methodology is sound and your conclusions are reliable.

通過嚴格的測試方法評估和比較 ML 模型性能 來源：eddiebe147/claude-settings。

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