Can this skill run code inside a notebook?

Yes, it utilizes the 'jupyter nbconvert --execute' command to run notebooks programmatically and save the results back to the file.

Can I convert notebooks to other formats?

Absolutely. It supports converting Jupyter notebooks into Python scripts, HTML pages, and Markdown documents using the nbconvert utility.

How does it modify notebook cells?

The skill treats .ipynb files as JSON objects, allowing Claude to precisely target and edit the source field of specific cells within the notebook structure.

Is it possible to clear outputs before pushing to Git?

Yes, the skill includes logic to programmatically strip all output data and execution counts, which is a best practice for versioning notebooks.

Jupyter Notebook Manager

Name: Jupyter Notebook Manager
Author: OpenHands

byOpenHands

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Data Science & ML

Manages Jupyter notebooks programmatically by reading, editing, executing, and converting .ipynb files for data science workflows.

About

This skill empowers Claude to interact directly with Jupyter notebooks as JSON structures, allowing for precise programmatic manipulation of code, markdown, and raw cells. It provides essential patterns for executing notebooks in place, clearing bulky output data, and converting files to various formats like Python scripts, HTML, or Markdown using nbconvert. Ideal for data scientists and researchers, this skill streamlines the automation of notebook-based workflows, enabling Claude to perform complex edits and conversions without requiring a manual UI session.

Key Features

Search capabilities within notebook JSON structures
Format conversion to Python scripts, HTML, and Markdown
Programmatic cell modification for code and markdown
40 GitHub stars
In-place notebook execution via nbconvert
Automated clearing of cell outputs and execution counts

Use Cases

Converting research notebooks into production-ready Python scripts
Automating the cleaning of data science notebooks before version control commits
Programmatically updating specific parameters or code cells across multiple experimental notebooks

About

Key Features

Search capabilities within notebook JSON structures
Format conversion to Python scripts, HTML, and Markdown
Programmatic cell modification for code and markdown
40 GitHub stars
In-place notebook execution via nbconvert
Automated clearing of cell outputs and execution counts

Use Cases

Converting research notebooks into production-ready Python scripts
Automating the cleaning of data science notebooks before version control commits
Programmatically updating specific parameters or code cells across multiple experimental notebooks