
Explore and query any dataset annotated with a Frictionless Data Package descriptor (datapackage.json). Use this skill whenever a user wants to discover what tables or resources a dataset contains, look up column names and descriptions, surface usage warnings embedded in metadata, or understand how to load data from Parquet files, DuckDB or SQLite databases, or CSV files described by a datapackage.json. Also use when the user has a datapackage.json and wants to know what's in it, how to query it efficiently, or how to connect its metadata to actual data files. Pairs well with dataset-specific skills (like `pudl`) that layer domain knowledge on top.
Full-stack development guidance for the PUDL project, covering contributor workflows, local ETL and Dagster development, metadata/schema changes, dbt and pytest validation, and data-oriented documentation context (data access, data dictionaries, data sources, and methodology).
Access PUDL table data plus table/column/source metadata in Jupyter or Marimo notebooks for debugging and visualization. Use when users ask what a table contains, how to read it, or how columns are defined.