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jupyter-notebooklisted

Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.
bingran-you/bingran-you · ★ 1 · Data & Documents · score 62
Install: claude install-skill bingran-you/bingran-you
# Jupyter Notebook Skill Create clean, reproducible Jupyter notebooks for two primary modes: - Experiments and exploratory analysis - Tutorials and teaching-oriented walkthroughs Prefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes. ## When to use - Create a new `.ipynb` notebook from scratch. - Convert rough notes or scripts into a structured notebook. - Refactor an existing notebook to be more reproducible and skimmable. - Build experiments or tutorials that will be read or re-run by other people. ## Decision tree - If the request is exploratory, analytical, or hypothesis-driven, choose `experiment`. - If the request is instructional, step-by-step, or audience-specific, choose `tutorial`. - If editing an existing notebook, treat it as a refactor: preserve intent and improve structure. ## Skill path (set once) ```bash export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}" export JUPYTER_NOTEBOOK_CLI="$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py" ``` User-scoped skills install under `$CODEX_HOME/skills` (default: `~/.codex/skills`). ## Workflow 1. Lock the intent. Identify the notebook kind: `experiment` or `tutorial`. Capture the objective, audience, and what "done" looks like. 2. Scaffold from the template. Use the helper script to avoid hand-authoring raw notebook JSON. ```bash uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \ --kind experiment \ --title "Compare prompt variants" \ --out output/jup