jupyter-notebook

Topics in the source

• Jupyter Notebook Skill
• When to use
• Decision tree
• Skill path (set once)
• Workflow
• Templates and helper script
• Temp and output conventions
• Dependencies (install only when needed)

Create clean, reproducible Jupyter notebooks for two primary modes: Experiments and exploratory analysis Tutorials and teaching-oriented walkthroughs Prefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes. Create a new .ipynb notebook from scratch. Convert rough notes or scripts into a structured notebook. Refactor an existing notebook to be more reproducible and skimmable. Build experiments or tutorials that will be read or re-run by other people. If the request is exploratory, analytical, or hypothesis-driven, choose experiment. If the request is instructional, step-by-step, or audience-specific, choose tutorial. If editing an existing notebook, treat it as a refactor: preserve intent and improve structure. User-scoped skills install under $CODEXHOME/skills (default: /.codex/skills). 1. Lock the intent. Identify the notebook kind: experiment or tutorial. Capture the objective, audience, and what "done" looks like. 2. Scaffold from the template. Use the helper script to avoid hand-authoring raw notebook JSON. 3. Fill the notebook with small, runnable steps. Keep each code cell focused on one step. Add short markdown cells that explain t

This is an excerpt. Refer to the complete source and its current requirements.