How does md2ipynb handle code blocks in Markdown?

It identifies specific languages like Python and SQL to create executable code cells in the output notebook, while keeping other languages within standard Markdown cells.

Can I define where new cells start in the notebook?

Yes, use the standard Markdown horizontal rule (three dashes) as a delimiter to signal the end of one cell and the beginning of the next.

What dependencies are required to run this skill?

The conversion script relies on the nbformat Python library, which can be handled automatically by running the command through uvx.

Does it clean up file metadata like YAML front matter?

Yes, the tool automatically detects and removes the first YAML front matter block to ensure your Jupyter Notebook starts with clean content.

Can I extract languages other than Python and SQL?

Yes, you can customize which languages are converted into code cells by using the --code-languages CLI option followed by a comma-separated list.

Markdown to Jupyter Converter

Name: Markdown to Jupyter Converter
Author: haggler09

byhaggler09

0•

Data Science & ML

Converts Markdown files into interactive Jupyter Notebooks by intelligently splitting sections and extracting code blocks.

The md2ipynb skill enables Claude to bridge the gap between static documentation and interactive environments by transforming Markdown files into fully functional Jupyter Notebooks (.ipynb). It leverages a specialized parsing logic that recognizes horizontal rules (three dashes) as cell delimiters and automatically identifies Python or SQL fenced code blocks to create executable code cells. By handling YAML front matter removal and preserving internal formatting, it provides a seamless workflow for developers and data scientists looking to turn tutorials, guides, or structured notes into reproducible data science experiments or interactive demonstrations.

Key Features

01Seamless YAML front matter removal for clean notebook headers

020 GitHub stars

03Intelligent cell splitting using three-dash horizontal rule delimiters

04Automatic extraction of Python and SQL code blocks into executable cells

05Preservation of markdown formatting and internal code block structure

06Customizable language extraction via command-line options

Use Cases

01Converting technical blog posts or tutorials into interactive learning environments

02Transforming static project documentation into reproducible data science experiments

03Rapidly prototyping SQL queries and Python analysis from Markdown-based notes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add haggler09/claude-haggler-skills md2ipynb

For use in Claude.ai and ChatGPT

Download Skill