Read, edit, execute, and debug Jupyter notebooks with Python code.
npx skills add https://github.com/Ming-Kai-LC/fyp-project --skill jupyter-ming-kai-lc
Please help me install this Agent Skill. Skill: jupyter Source: https://github.com/Ming-Kai-LC/fyp-project/tree/main/FYP_Code/.claude/skills/jupyter Command: npx skills add https://github.com/Ming-Kai-LC/fyp-project --skill jupyter-ming-kai-lc
This Skill helps data scientists and researchers quickly reason about, edit, and run code inside Jupyter notebooks, reducing context-switching and manual edits.
Open a notebook file (e.g., my_analysis.ipynb) and run a small code cell to print summary statistics, using the notebook's kernel to validate changes.
High-intent search queries and answers about installing and using this skill.
Edit cells by replacing, inserting, or deleting code, then execute Python code in the active kernel to test changes immediately. This lets you modify notebook logic and validate results without manual edits.
Yes, you can read complete notebook contents—code cells, markdown, and execution outputs—to understand context and dependencies before making changes or running analysis.
Debug specific notebook sections and generate inline explanations and comments to improve readability while preserving execution order and reproducibility across cells.
Execute Python code directly in the notebook's kernel to test ideas and fixes in place, eliminating context-switching and enabling rapid iteration on analysis workflows.
No, the Skill preserves execution order and reproducibility automatically, so you can edit and execute cells while maintaining kernel state and notebook integrity.
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