Does this skill support automated documentation?

Yes, it includes a specific stage for generating ASCII workflow diagrams and function relationship trees to help explain script logic and structure.

How are code cells defined within the Python scripts?

Cells are defined using standard # %% markers, which allows the script to remain runnable as a standard Python file while supporting notebook-style execution.

What is the primary source of truth in this pipeline?

The standalone Python script located in the scripts/ directory is the primary source of truth, which is then used to generate notebooks and documentation.

How does it handle project-wide settings?

It utilizes a 1-config.yaml file to manage paths, project roots, and specific analysis parameters across the entire pipeline.

Can I use this with VS Code or standard Jupyter interfaces?

Absolutely. The generated .ipynb files are fully compatible with Jupyter Notebook, JupyterLab, and the VS Code Interactive Window.

Python Analysis Pipeline

Name: Python Analysis Pipeline
Author: jluo41

byjluo41

0•

데이터 과학 및 ML

Manages a complete 4-stage pipeline from Python scripts to interactive notebooks and automated markdown documentation.

The Notebook-Cell-Python skill provides a structured framework for research and evaluation analysis, bridging the gap between standalone Python scripts and interactive Jupyter environments. It enforces a professional workflow where scripts serve as the single source of truth, utilizing cell-based markers to facilitate seamless conversion into notebooks, full-content markdowns, and LLM-generated documentation. By standardizing configuration management and relative path handling, this skill ensures that complex data analyses remain reproducible, well-documented, and easy to explore through every stage of the development lifecycle.

주요 기능

01Centralized configuration management via YAML for reproducible research

02Automatic conversion tools to sync standalone scripts with interactive notebooks

03Cell-based script structure using standard # %% markers for modular execution

04Automated 4-stage pipeline: Script → Notebook → Markdown → Documentation

050 GitHub stars

06LLM-ready documentation generation featuring ASCII workflow diagrams and function trees

사용 사례

01Generating automated project documentation and architectural diagrams from code

02Establishing a reproducible model evaluation and data analysis workflow

03Converting standalone research scripts into interactive notebooks for debugging and exploration

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jluo41/tools notebook-cell-python

For use in Claude.ai and ChatGPT

Download Skill