About

Imported from practicalswan/agent-skills (jupyter-notebook/SKILL.md). Install upstream with npx skills add practicalswan/agent-skills --skill jupyter-notebook. Copyright stays with the author.

Jupyter Notebook Skill

Name: jupyter-notebook
Author: practicalswan

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.

When to use

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.

Decision tree

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.

Skill path (set once)

export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export JUPYTER_NOTEBOOK_CLI="$CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py"

User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills).

Workflow

Lock the intent. Identify the notebook kind: experiment or tutorial. Capture the objective, audience, and what "done" looks like.
Scaffold from the template. Use the helper script to avoid hand-authoring raw notebook JSON.

uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind experiment \
  --title "Compare prompt variants" \
  --out output/jupyter-notebook/compare-prompt-variants.ipynb

uv run --python 3.12 python "$JUPYTER_NOTEBOOK_CLI" \
  --kind tutorial \
  --title "Intro to embeddings" \
  --out output/jupyter-notebook/intro-to-embeddings.ipynb

Fill the notebook with small, runnable steps. Keep each code cell focused on one step. Add short markdown cells that explain the purpose and expected result. Avoid large, noisy outputs when a short summary works.
Apply the right pattern. For experiments, follow references/experiment-patterns.md. For tutorials, follow references/tutorial-patterns.md.
Edit safely when working with existing notebooks. Preserve the notebook structure; avoid reordering cells unless it improves the top-to-bottom story. Prefer targeted edits over full rewrites. If you must edit raw JSON, review references/notebook-structure.md first.
Validate the result. Run the notebook top-to-bottom when the environment allows. If execution is not possible, say so explicitly and call out how to validate locally. Use the final pass checklist in references/quality-checklist.md.

Templates and helper script

Templates live in assets/experiment-template.ipynb and assets/tutorial-template.ipynb.
The helper script loads a template, updates the title cell, and writes a notebook.

Script path:

$JUPYTER_NOTEBOOK_CLI (installed default: $CODEX_HOME/skills/jupyter-notebook/scripts/new_notebook.py)

Temp and output conventions

Use tmp/jupyter-notebook/ for intermediate files; delete when done.
Write final artifacts under output/jupyter-notebook/ when working in this repo.
Use stable, descriptive filenames (for example, ablation-temperature.ipynb).

Dependencies (install only when needed)

Prefer uv for dependency management.

Optional Python packages for local notebook execution:

uv pip install jupyterlab ipykernel

The bundled scaffold script uses only the Python standard library and does not require extra dependencies.

Environment

No required environment variables.

Reference map

references/experiment-patterns.md: experiment structure and heuristics.
references/tutorial-patterns.md: tutorial structure and teaching flow.
references/notebook-structure.md: notebook JSON shape and safe editing rules.
references/quality-checklist.md: final validation checklist.

Anti-Patterns

Hand-authoring raw notebook JSON when the bundled scaffold or a targeted cell edit would avoid avoidable formatting mistakes.
Packing large exploratory leaps into one noisy cell instead of building small, runnable notebook steps with short narrative bridges.
Presenting a notebook as validated when it has not been run top-to-bottom or the execution limitation has not been disclosed.

Verification Protocol

Pass/fail: the notebook opens successfully and the structure, title, and requested sections match the chosen experiment or tutorial pattern.
Pressure test: execute the notebook top-to-bottom when the environment allows, or validate the JSON plus template structure and call out any runtime gap explicitly.
Success metric: no malformed notebook JSON and a clear top-to-bottom flow with runnable or clearly marked cells.

Cross-Client Portability

This skill is written to stay usable across GitHub Copilot, Claude Code, and Codex.

GitHub Copilot: keep the folder in a Copilot-visible skill path or wrap the workflow in project instructions when folder discovery is unavailable.
Claude Code: keep the folder in a local skills directory or a compatible plugin source.
Codex: install or sync the folder into $CODEX_HOME/skills/jupyter-notebook and restart Codex after major changes.

MCP Availability And Fallback

No dedicated MCP server is required for the normal workflow in this skill.

Preferred MCP Server: None required Fallback prompt: Use the bundled new_notebook.py scaffold, local Jupyter tooling, and notebook execution logs as the fallback evidence path when no notebook-aware MCP surface is available.

Related Skills

codebase-to-course
notebooklm-management
excel-sheet
documentation-authoring

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/practicalswan-agent-skills-jupyter-notebook/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

practicalswan-agent-skills-jupyter-notebook.ocm.jsonjson

{
  "ocm": "1",
  "id": "practicalswan-agent-skills-jupyter-notebook",
  "kind": "skill",
  "name": "jupyter-notebook",
  "description": "Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and helper script for reproducible notebook structure and safer editing.",
  "publisher": "practicalswan",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "jupyter",
      "notebook",
      "python",
      "experiments",
      "tutorials",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and helper script for reproducible notebook structure and safer editing."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/practicalswan/agent-skills",
      "path": "jupyter-notebook/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/practicalswan/agent-skills/blob/HEAD/jupyter-notebook/SKILL.md",
      "key": "practicalswan/agent-skills/jupyter-notebook/SKILL.md"
    }
  },
  "instructions": "# Jupyter Notebook Skill\n\nCreate clean, reproducible Jupyter notebooks for two primary modes:\n\n- Experiments and exploratory analysis\n- Tutorials and teaching-oriented walkthroughs\n\nPrefer the bundled templates and the helper script for consistent structure and fewer JSON mistakes.\n\n## When to use\n- Create a new `.ipynb` notebook from scratch.\n- Convert rough notes or scripts into a structured notebook.\n- Refactor an existing notebook to be more reproducible and skimmable.\n- Build experiments or tutorials that will be read or re-run by other people.\n\n## Decision tree\n- If the request is explor",
  "cost": {
    "context_tokens": 1427
  }
}

Fetch it by URL: GET /api/v1/registry/practicalswan-agent-skills-jupyter-notebook/manifest?version=1.0.0

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