| name | datarobot-feature-engineering |
| description | Guidance for feature engineering, feature discovery, feature importance analysis, and understanding DataRobot's automated feature engineering capabilities. Use when working with feature engineering, feature discovery, or analyzing feature importance in DataRobot. |
| metadata | {"category":"data","source":{"repository":"https://github.com/datarobot-oss/datarobot-agent-skills","path":"skills/datarobot-feature-engineering","license_path":"LICENSE","commit":"f4b3c29db60e1d735285a6f51328a69a2b500338"}} |
DataRobot Feature Engineering Skill
This skill provides guidance for working with features in DataRobot, including understanding automated feature engineering, analyzing feature importance, and optimizing feature sets.
Quick Start
Most common use case: Analyze feature importance for a model
- Get feature importance:
get_feature_importance(model_id) to get importance scores
- Analyze top features: Sort by importance and identify key drivers
- Export feature list:
export_feature_list(project_id) to document features
Example: "Show me the top 10 most important features for model xyz123"
When to use this skill
Use this skill when you need to:
- Understand what features DataRobot creates automatically
- Analyze feature importance for models
- Discover which features drive predictions
- Optimize feature sets for better performance
- Understand feature types and transformations
- Export feature lists and definitions
