Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.
Scanned 6/2/2026
Install via CLI
openskills install majiayu000/claude-skill-registry---
name: feature-engineering-kit
description: Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.
---
# Feature Engineering Kit
Automated feature engineering with encodings, scaling, and transformations.
## Features
- **Encodings**: One-hot, label, target encoding
- **Scaling**: Standard, min-max, robust scaling
- **Polynomial Features**: Generate interactions
- **Binning**: Discretize continuous features
- **Date Features**: Extract time-based features
- **Text Features**: TF-IDF, word counts
- **Missing Value Handling**: Imputation strategies
## CLI Usage
```bash
python feature_engineering.py --data train.csv --output engineered.csv --config config.json
```
## Dependencies
- scikit-learn>=1.3.0
- pandas>=2.0.0
- numpy>=1.24.0
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...