Jupyter Notebook Guide

SkillFiles & storage

Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Jupyter Notebook Guide skill

What this skill tells your AI

The instructions your AI receives, as published by openhands/extensions in skills/jupyter/SKILL.md and read by ahel’s review.

Notebooks are JSON files. Cells are in nb['cells'], each has source (list of strings) and cell_type ('code', 'markdown', or 'raw').

Modifying Notebooks

import json
with open('notebook.ipynb') as f:
    nb = json.load(f)
# Modify nb['cells'][i]['source'], then:
with open('notebook.ipynb', 'w') as f:
    json.dump(nb, f, indent=1)

Executing & Converting

jupyter nbconvert --to notebook --execute --inplace notebook.ipynb  # Execute in place
jupyter nbconvert --to html notebook.ipynb      # Convert to HTML
jupyter nbconvert --to script notebook.ipynb    # Convert to Python
jupyter nbconvert --to markdown notebook.ipynb  # Convert to Markdown

Finding Code

grep -n "search_term" notebook.ipynb

PowerShell equivalent:

Select-String -Path notebook.ipynb -Pattern "search_term"

Cell Structure

# Code cell
{"cell_type": "code", "execution_count": None, "metadata": {}, "outputs": [], "source": ["code\n"]}
# Markdown cell
{"cell_type": "markdown", "metadata": {}, "source": ["# Title\n"]}

Clear Outputs

for cell in nb['cells']:
    if cell['cell_type'] == 'code':
        cell['outputs'] = []
        cell['execution_count'] = None

Signals

GitHub stars
144
Forks
86
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
jupyter-openhands
Source
github.com/openhands/extensions
Jupyter Notebook Guide by openhands: Skill · ahel