engineering-features-for-machine-learning

Quick Review

This skill provides a reasonable framework for feature engineering tasks with clear use cases and examples. The description adequately covers what the skill does (creating, selecting, and transforming features), though it could be more specific about invocation patterns. Task knowledge is moderate - while the SKILL.md references scripts and components that would contain implementation details, the main documentation remains somewhat generic. Structure is acceptable with logical sections, though there's redundancy (duplicate 'Overview' text, multiple README.md files in the tree). Novelty is modest - while feature engineering is useful, many of these tasks (scaling, encoding, feature selection) are straightforward for a capable CLI agent with standard libraries like scikit-learn, though the integrated pipeline approach and feature importance analysis add some value. The skill would benefit from more concrete technical details about the actual methods used and clearer trigger conditions.