Localized reading guide
jupyter-notebookPurpose, usage and source
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.
Source retrieved:
- Source repository
- openai/skills
- SKILL.md
skills/.curated/jupyter-notebook/SKILL.md- Repository stars
- 28,420
- Repository updated
- 2026-10-29
- Categories
- Other
- Last collected
License: License file needs review
Workflow excerpts are reading aids, not executable instructions from Codez. No third-party Skill was run to produce this page.
The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.
What this Skill does
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.
How the upstream workflow works
Workflow
Lock the intent. Identify the notebook kind: experiment or tutorial. Capture the objective, audience, and what "done" looks like. Scaffold from the template. Use the helper script to avoid hand-authoring raw notebook JSON. 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. Apply the right pattern. For experiments, follow references/experiment-patterns.md. For tutorials, follow references/tutorial-patterns.md.
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.
Jupyter Notebook Skill
Create clean, reproducible Jupyter notebooks for two primary modes: Experiments and exploratory analysis
Upstream passage · L7 ↗export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export JUPYTER_NOTEBOOK_CLI="$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py"Requirements and setup
Dependencies (install only when needed)
Prefer uv for dependency management. Optional Python packages for local notebook execution:
Limits and quality checks
No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.
Start with a safe trial
- Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
- Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
- Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
- Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.
Read further in the source
Related Skills
Translation and scope
This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.
This introduction refers to the pinned version below; current repository activity and collection time are shown separately.
- Pinned source
- Read the original ↗
- Source retrieved
- Source commit
49f948faa9258a0c61caceaf225e179651397431- Source SHA-256
62f102e8554b25716dccef0ffab4572d4e3eaf05ccc76562d33a065bc9c521fb