Data Science skills for AI agents
8 practitioner-grade data science skills, each a focused Markdown document your agent loads into context on demand. Search them from Claude Desktop, Cursor or any MCP client, or pull one with the CLI.
All 8 skills
- Data Cleaning
Expert guidance on data cleaning and preprocessing techniques for preparing raw data for analysis and modeling.
230 lines - Feature Engineering
Expert guidance on feature engineering patterns for transforming raw data into predictive ML features.
184 lines - Jupyter
Expert guidance on Jupyter notebooks for interactive data exploration, documentation, and reproducible analysis.
174 lines - Matplotlib
Expert guidance on Matplotlib for creating static, animated, and interactive visualizations in Python.
164 lines - Numpy
Expert guidance on NumPy for numerical computing, array operations, and linear algebra in Python.
171 lines - Pandas
Expert guidance on Pandas for tabular data manipulation, transformation, and analysis in Python.
172 lines - Polars
Expert guidance on Polars for high-performance dataframe operations with a lazy query engine in Python.
169 lines - Scikit Learn
Expert guidance on scikit-learn for building, evaluating, and deploying machine learning models in Python.
175 lines