MCPInstall

jupyter-notebook

by microsoft OfficialAI & Agents

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 newnotebook.py to generate a clean starting notebook.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/microsoft/ai-agents-for-beginners --skill jupyter-notebook
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads jupyter-notebook automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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)

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.

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

  1. 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.

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

  3. 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.

  4. 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 (installed default: $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: experiment structure and heuristics.
  • references/tutorial-patterns.md: tutorial structure and teaching flow.
  • references/notebook-structure.md: notebook JSON shape and safe editing rules.
  • references/quality-checklist.md: final validation checklist.

FAQ

What does the jupyter-notebook skill do?

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 newnotebook.py to generate a clean starting notebook.

How do I install jupyter-notebook?

Run npx skills add https://github.com/microsoft/ai-agents-for-beginners --skill jupyter-notebook in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/jupyter-notebook/ (personal) or .claude/skills/jupyter-notebook/ (project).

Which AI agents can use jupyter-notebook?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is jupyter-notebook safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains jupyter-notebook?

It is published by microsoft in microsoft/ai-agents-for-beginners, and it is an official skill from the maker of the technology it covers. It has 92 recorded installs.

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