Related Skills

Use $validate-data when notebook results support a recommendation, shared claim, or decision.

Jupyter Notebooks

Create clean, reproducible Jupyter notebooks that are easy to skim, rerun, and handoff. Treat the notebook as a reader-facing analysis artifact, not a scratchpad dump. Notebook work is not complete until the notebook executes successfully top-to-bottom, or the execution gap is called out with the exact validation steps needed to reproduce it.

Workflow

1. Lock the notebook mode and scope.

   Decide whether the notebook is an analysis report, experiment log, diagnostic notebook, data-quality check, market-sizing calculation, model exploration, tutorial, or companion artifact for a report. Identify the reader, decision, expected handoff, required inputs, and whether the task calls for a new notebook or targeted edits to an existing one.

2. Inspect or scaffold with notebook-safe tooling.