Notebook AI Agents Skill (Marimo First)
Build narrative-first, reproducible notebooks with strict run-all validation and clean data loading patterns. Prefer Marimo for new notebooks; support Jupyter only when needed for existing .ipynb files.
Instructions
- Prefer Marimo for new work. Create a
.pynotebook and keep cells small and deterministic. - Outline the notebook (purpose, data sources, analysis steps, outputs) before coding.
- Use project-relative paths and DuckDB for data loading (TSV/Parquet preferred).
- Build plots with the shared style rules.
- Validate by running the notebook end-to-end (Marimo:
marimo run; Jupyter: restart kernel + run all).
Quick Reference
| Task | Action |
|---|---|
| Marimo docs | https://docs.marimo.io/ |
| Jupyter (legacy) | See docs/notebook_structure.md |
| Pixi + Jupyter (legacy) | See docs/pixi_jupyter.md |
| Data loading | See docs/data_loading_duckdb.md |
| Plot styling | See docs/plot_style.md |
| Validation | See docs/verification.md |
| Templates (legacy) | templates/kiss_notebook_template.py |
Input Requirements
- Notebook scope and goals
- Data file paths (TSV/Parquet preferred)
- Python environment (Pixi recommended)
- Marimo installed (preferred) or Jupyter available (legacy)
Output
- Reproducible notebook with narrative markdown
- Validated run-all execution
- Plots and tables suitable for reporting
Quality Gates
- Narrative text precedes code for each major step
- All cells run top-to-bottom without hidden state
- Data paths are project-relative and verified
- Plots are labeled, readable, and consistent
Examples
Example 1: Run a Marimo notebook
marimo run notebooks/analysis.py
Example 2: Execute a Jupyter notebook (legacy)
python scripts/execute_notebook.py path/to/notebook.ipynb
Troubleshooting
Issue: Marimo fails to run due to missing dependencies Solution: Install required packages in the Pixi environment and re-run.
Issue: Jupyter notebook fails on restart Solution: Remove hidden state, re-run from a clean kernel, and fix warnings.