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Official agent skill

Jupyter Notebook

by microsoft in microsoft/ai-agents-for-beginners

當使用者要求建立、搭建或編輯用於實驗、探索或教學的 Jupyter 筆記本 (.ipynb) 時使用；優先採用內建範本並執行輔助腳本 newnotebook.py 以產生一個乾淨的起始筆記本。

OfficialMITAuto-check passedData & Analytics

Install Jupyter Notebook

skills CLI
$ npx skills add microsoft/ai-agents-for-beginners --skill jupyter-notebook -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/ai-agents-for-beginners jupyter-notebook --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/ai-agents-for-beginners.git skills-src && mkdir -p .claude/skills && cp -r skills-src/translations/zh-MO/.agents/skills/jupyter-notebook .claude/skills/jupyter-notebook && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
jupyter-notebook
GitHub stars
77k
Token cost
~795 tokens
SKILL.md length
221 words
Files
7 (incl. references, assets)
Skills in repo
122
Repo updated
First seen
Licence
MIT

At a glance

當使用者要求建立、搭建或編輯用於實驗、探索或教學的 Jupyter 筆記本 (.ipynb) 時使用；優先採用內建範本並執行輔助腳本 newnotebook.py 以產生一個乾淨的起始筆記本。

  • Tasks that involve Jupyter notebooks
  • SKILL.md covers 何時使用, 決策樹, 技能路徑（設定一次） and 工作流程, plus 5 more sections
  • Calls uv

What it does

Jupyter Notebook is an agent skill from microsoft/ai-agents-for-beginners, published by the product's own GitHub organization. 當使用者要求建立、搭建或編輯用於實驗、探索或教學的 Jupyter 筆記本 (.ipynb) 時使用；優先採用內建範本並執行輔助腳本 newnotebook.py 以產生一個乾淨的起始筆記本。

Its SKILL.md is about 800 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files and assets (for example `references/experiment-patterns.md`, `references/notebook-structure.md` and `references/quality-checklist.md`).

It sits in Data & Analytics, covering Jupyter notebooks. It works with Jupyter. The repository describes itself as: 18 Lessons to Get Started Building AI Agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Jupyter notebooks

Example prompts

  • “/jupyter-notebook”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit ff2ba66. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Jupyter Notebook loads about 795 tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 30 tokens; SKILL.md has 221 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~795
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/ai-agents-for-beginners at commit ff2ba66, republished under its MIT licence (© microsoft). 221 words, ~795 tokens.

Download SKILL.mdSave it as .claude/skills/jupyter-notebook/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
jupyter-notebook
description
當使用者要求建立、搭建或編輯用於實驗、探索或教學的 Jupyter 筆記本 (`.ipynb`) 時使用；優先採用內建範本並執行輔助腳本 `new_notebook.py` 以產生一個乾淨的起始筆記本。

Jupyter Notebook 技能

為兩種主要模式建立乾淨、可重現的 Jupyter 筆記本：

  • 實驗與探索性分析
  • 教學及導覽式示範

優先使用隨附的範本和輔助腳本，以獲得一致的結構並減少 JSON 錯誤。

何時使用

  • 從頭建立新的 .ipynb 筆記本。
  • 將草稿筆記或腳本轉換為結構化的筆記本。
  • 重構現有的筆記本，使其更具可重現性且易於瀏覽。
  • 建立會被他人閱讀或重新執行的實驗或教學範例。

決策樹

  • 如果請求是探索性、分析性或以假設為驅動，選擇 experiment。
  • 如果請求是教學型、逐步或針對特定受眾，選擇 tutorial。
  • 如果編輯現有筆記本，將其視為重構：保留意圖並改進結構。

技能路徑（設定一次）

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).

工作流程

  1. 鎖定意圖。 Identify the notebook kind: experiment or tutorial. Capture the objective, audience, and what "done" looks like.

  2. 從範本建立骨架。 Use the helper script to avoid hand-authoring raw notebook JSON.

bash
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind experiment \
  --title "Compare prompt variants" \
  --out output/jupyter-notebook/compare-prompt-variants.ipynb
bash
uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind tutorial \
  --title "Intro to embeddings" \
  --out output/jupyter-notebook/intro-to-embeddings.ipynb

  1. 用小而可執行的步驟填充筆記本。 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. 套用正確的範式。 For experiments, follow references/experiment-patterns.md. For tutorials, follow references/tutorial-patterns.md.

  3. 在處理現有筆記本時安全地編輯。 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. 驗證結果。 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.

範本與輔助腳本

  • 範本位於 assets/experiment-template.ipynb 與 assets/tutorial-template.ipynb。
  • 輔助腳本會載入範本、更新標題儲存格，並寫出筆記本。

Script path:

  • $JUPYTER_NOTEBOOK_CLI (預設安裝位置: $CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py)

暫存與輸出慣例

  • 使用 tmp/jupyter-notebook/ 做為中間檔案位置；完成後刪除。
  • 在此 repo 中工作時，將最終產物寫在 output/jupyter-notebook/ 下。
  • 使用穩定且具描述性的檔名（例如，ablation-temperature.ipynb）。

相依套件（僅在需要時安裝）

Prefer uv for dependency management.

Optional Python packages for local notebook execution:

bash
uv pip install jupyterlab ipykernel

隨附的骨架腳本僅使用 Python 標準函式庫，不需要額外相依套件。

環境

沒有必須的環境變數。

參考地圖

  • references/experiment-patterns.md: 實驗結構與啟發式準則。
  • references/tutorial-patterns.md: 教學結構與教學流程。
  • references/notebook-structure.md: 筆記本 JSON 格式與安全編輯規則。
  • references/quality-checklist.md: 最終驗證檢查清單。
<!-- CO-OP TRANSLATOR DISCLAIMER START -->

免責聲明： 本文件已使用 AI 翻譯服務 Co-op Translator（https://github.com/Azure/co-op-translator）進行翻譯。儘管我們力求準確，但請注意，自動翻譯可能包含錯誤或不準確之處。原文之母語版本應視為具權威性的來源。若涉及重要資訊，建議採用專業人工翻譯。我們對因使用本翻譯而產生的任何誤解或曲解不承擔任何責任。

<!-- CO-OP TRANSLATOR DISCLAIMER END -->

© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references, assets) in translations/zh-MO/.agents/skills/jupyter-notebook of microsoft/ai-agents-for-beginners.

  • SKILL.md
  • assets/experiment-template.ipynb
  • assets/tutorial-template.ipynb
  • references/experiment-patterns.md
  • references/notebook-structure.md
  • references/quality-checklist.md
  • references/tutorial-patterns.md

Open the folder on GitHubat commit ff2ba66

Compare with similar skills

Jupyter Notebook next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Jupyter Notebook compared with similar skills
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Jupyter Notebook this skillmicrosoft/ai-agents-for-beginners77k—~795Automated safety check: PassMIT
Notebook For ExperimentJetBrains/intellij-community21k—~4.4kAutomated safety check: WarnCustom licence
Jupyter To Marimoericmjl/llamabot1832 repos~475Automated safety check: PassNone
Nbreviewawdeorio/dotfiles102—~2.2kAutomated safety check: PassNone
Save Research Notebooknapjon/krisk117—~702Automated safety check: PassBSD-3-Clause
Doc Releasemindspore-ai/docs167—~4.8kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Jupyter Notebook

What does Jupyter Notebook do?

當使用者要求建立、搭建或編輯用於實驗、探索或教學的 Jupyter 筆記本 (.ipynb) 時使用；優先採用內建範本並執行輔助腳本 newnotebook.py 以產生一個乾淨的起始筆記本。. Jupyter Notebook is an agent skill from microsoft/ai-agents-for-beginners, published by the product's own GitHub organization.

When should I use Jupyter Notebook?

Jupyter Notebook fits situations like: tasks that involve Jupyter notebooks.

How do I install Jupyter Notebook in Claude Code?

Run `npx skills add microsoft/ai-agents-for-beginners --skill jupyter-notebook -a claude-code`. Or copy the skill folder (translations/zh-MO/.agents/skills/jupyter-notebook in microsoft/ai-agents-for-beginners) into .claude/skills/jupyter-notebook in your project. Claude Code loads it when a task matches its description.

How do I install Jupyter Notebook in Codex?

Run `npx skills add microsoft/ai-agents-for-beginners --skill jupyter-notebook -a codex`. Or copy the skill folder (translations/zh-MO/.agents/skills/jupyter-notebook in microsoft/ai-agents-for-beginners) into .agents/skills/jupyter-notebook in your project. Codex loads it when a task matches its description.

Can I use Jupyter Notebook in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/ai-agents-for-beginners --skill jupyter-notebook -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jupyter-notebook, .gemini/skills/jupyter-notebook, .github/skills/jupyter-notebook and .opencode/skills/jupyter-notebook in your project.

What does Jupyter Notebook need to run?

Going by SKILL.md and its folder, Jupyter Notebook needs the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Jupyter Notebook access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Jupyter Notebook safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Jupyter Notebook use?

Jupyter Notebook is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Jupyter Notebook use?

About 795 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Jupyter Notebook?

Skills that share tags, products or a category with Jupyter Notebook: Notebook For Experiment (JetBrains/intellij-community, 21k stars), Jupyter To Marimo (ericmjl/llamabot, 183 stars), Nbreview (awdeorio/dotfiles, 102 stars) and Save Research Notebook (napjon/krisk, 117 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Jupyter Notebook?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/ai-agents-for-beginners, which has 76,795 GitHub stars. The repository holds 122 skills in this directory. The repository was last updated on October 9, 2026.

Source: microsoft/ai-agents-for-beginners on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.