Agent skill
feature-engineering-kit
Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/feature-engineering-kit
SKILL.md
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
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
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Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
agent-ops-state
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agent-ops-spec
Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
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agent-ops-testing
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
agent-ops-state
Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.
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