Generate Jupytext-based Markdown notebooks for reproducible analyses.
npx skills add https://github.com/dangeles/claude --skill notebook-writer
Please help me install this Agent Skill. Skill: notebook-writer Source: https://github.com/dangeles/claude/tree/main/claude-config/skills/notebook-writer Command: npx skills add https://github.com/dangeles/claude --skill notebook-writer
This skill helps researchers and data scientists create well-structured, reproducible Jupyter notebooks that document calculations, workflows, and results in a git-friendly format.
Create a Markdown notebook following the examples in the skill guide, then convert to IPYNB using python3 -m jupytext --to ipynb notebook.md and run it in Jupyter. This workflow keeps notebooks human-readable and version-controlled.
High-intent search queries and answers about installing and using this skill.
You can create reproducible Jupyter notebooks by writing Jupytext-based Markdown files with clear narrative and code cells, then converting them to IPYNB format using python3 -m jupytext --to ipynb. This keeps notebooks human-readable and git-friendly for collaboration.
Literate programming for data analysis combines narrative documentation and executable code within Markdown notebooks. This skill generates well-structured Jupytext files that document calculations, workflows, and parameterized sweeps for transparent, reproducible reporting.
Yes, you can convert Markdown notebooks to IPYNB format by running python3 -m jupytext --to ipynb notebook.md. This workflow enables end-to-end reproducibility by maintaining a human-readable source file while producing standard Jupyter outputs.
To document dependencies for reproducible data analysis, this skill provides templates that explicitly record the environment and dependencies alongside parameterized workflows. This ensures calculations and results can be recreated and verified.
Yes, Jupytext works with parameter sweeps by providing structured templates within Markdown notebooks. These templates support parameterized workflows and clear narrative documentation, enabling reproducible reporting for data scientists and researchers.
The best way to keep Jupyter notebooks git-friendly is authoring them as Jupytext Markdown files. This format tracks changes clearly in version control, avoiding large binary outputs, and easily converts to IPYNB for execution.
ninehillsConvert Jupyter Notebooks between .py and .ipynb formats.
tercumantanumutScaffold reproducible Jupyter notebooks from bundled templates.
fabioc-alohaPublish changed notebooks from VS Code to Microsoft Fabric via Azure DevOps Git.
edwinhuSynchronize Jupyter notebooks with plain text formats for Git version control.
