Jupyter Notebook

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.

uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind experiment \
  --title "Compare prompt variants" \
  --out output/jupyter-notebook/compare-prompt-variants.ipynb

uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind tutorial \
  --title "Intro to embeddings" \
  --out output/jupyter-notebook/intro-to-embeddings.ipynb

3. Fill the notebook with small, runnable steps. Keep each code cell focused on one step. Add short markdown cells that explain the purpose and expected result. Avoid large, noisy outputs when a short summary works.

4. Apply the right pattern. For experiments, follow references/experiment-patterns.md. For tutorials, follow references/tutorial-patterns.md.

5. Edit safely when working with existing notebooks. Preserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story. Prefer targeted edits over full rewrites. If you must edit raw JSON, review references/notebook-structure.md first.

6. Validate the result. Run the notebook top-to-bottom when the environment allows. If execution is not possible, say so explicitly and call out how to validate locally. Use the final pass checklist in references/quality-checklist.md.

Templates and helper script

• Templates live in assets/experiment-template.ipynb and assets/tutorial-template.ipynb.
• The helper script loads a template, updates the title cell, and writes a notebook.

Script path:

• $JUPYTER_NOTEBOOK_CLI（インストール時のデフォルト: $CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py）

Temp and output conventions

• Use tmp/jupyter-notebook/ for intermediate files; delete when done.
• Write final artifacts under output/jupyter-notebook/ when working in this repo.
• Use stable, descriptive filenames (for example, ablation-temperature.ipynb).

Dependencies (install only when needed)

Prefer uv for dependency management.

Optional Python packages for local notebook execution:

uv pip install jupyterlab ipykernel

The bundled scaffold script uses only the Python standard library and does not require extra dependencies.

Environment

No required environment variables.

Reference map

• references/experiment-patterns.md: 実験の構成と経験則。
• references/tutorial-patterns.md: チュートリアルの構成と教育的な流れ。
• references/notebook-structure.md: ノートブックJSONの構造と安全な編集ルール。
• references/quality-checklist.md: 最終検証チェックリスト。

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