Does this skill handle Google Colab specific features?

Yes, it provides specific implementation patterns for Colab-specific metadata, interactive form fields, and collapsible code sections using #@title.

Can it modify existing notebooks without corrupting the file?

Absolutely. It uses a safe read-modify-write pattern that targets specific cell IDs, ensuring the JSON structure remains valid and your data stays intact.

How does it handle multi-line code blocks in cells?

It strictly follows the .ipynb standard by formatting the 'source' field as an array of strings, with each line properly escaped and ending with a newline character.

Why are unique cell IDs important for this skill?

Unique IDs allow Claude to programmatically target, update, or delete specific cells within a notebook without relying on fragile index-based positions.

Is this skill limited to Python code cells?

No, it supports the creation and formatting of both code and markdown cells, including proper header formatting and section dividers for better documentation.

Jupyter Notebook Manager

Name: Jupyter Notebook Manager
Author: ali

byali

数据科学与机器学习

Programmatically creates, edits, and optimizes Jupyter and Google Colab notebooks with precise JSON formatting and metadata management.

关于

This skill enables Claude to function as a specialized notebook engineer, capable of generating complex .ipynb files from scratch or modifying existing ones with surgical precision. It handles the intricacies of the Jupyter JSON schema, including cell source arrays, metadata IDs, and Google Colab-specific enhancements like interactive form fields and collapsible sections. Whether you need to automate the creation of data science pipelines, inject new analysis steps into existing research notebooks, or ensure structural integrity across a library of interactive documents, this skill provides the necessary patterns for high-quality notebook manipulation.

主要功能

Safe editing patterns for inserting, updating, or deleting cells
Programmatic creation and modification of .ipynb JSON structures
Automated generation of standardized setup and configuration cells
0 GitHub stars
Support for Google Colab-specific form fields and collapsible sections
Precise management of cell metadata and unique descriptive IDs

使用场景

Generating standardized data science project templates for Google Colab
Converting raw Python scripts into well-documented, interactive Jupyter notebooks
Automating the injection of model evaluation code into existing research notebooks

关于

主要功能

Safe editing patterns for inserting, updating, or deleting cells
Programmatic creation and modification of .ipynb JSON structures
Automated generation of standardized setup and configuration cells
0 GitHub stars
Support for Google Colab-specific form fields and collapsible sections
Precise management of cell metadata and unique descriptive IDs

使用场景

Generating standardized data science project templates for Google Colab
Converting raw Python scripts into well-documented, interactive Jupyter notebooks
Automating the injection of model evaluation code into existing research notebooks