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Openai Jupyter Notebook

Checked
trailofbits·vlatest·ai-ml·CC-BY-SA-4.0

Execute Python code within Jupyter Notebooks using OpenAI's models, enabling interactive data exploration and model experimentation.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add trailofbits/skills-curated --skill openai-jupyter-notebook -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

trailofbits

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned trailofbits/skills-curated at 6d05be4889.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
6d05be4889
Manifest
plugins/openai-jupyter-notebook/skills/openai-jupyter-notebook/SKILL.md
Scanned
6 files, 291 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill allows AI agents to execute code within a Jupyter Notebook environment. It enables complex data analysis, model training, and interactive experimentation directly through the agent's interface. The agent can create new notebooks, load existing ones, and run cells containing Python code.

When to use it

  • Data Exploration: When you need an AI agent to analyze a dataset and generate visualizations or insights.
  • Model Development: For agents tasked with building and training machine learning models, requiring iterative coding and experimentation.
  • Reproducible Research: To ensure that complex analytical workflows are documented and easily reproducible.
  • Interactive Debugging: When you need an agent to debug code by running it step-by-step in a notebook environment.

Key capabilities

  • Jupyter Notebook execution
  • Python code support within notebooks
  • Creation of new Jupyter Notebooks
  • Loading and editing existing notebooks

Example prompts

  • "Create a new Jupyter Notebook named 'data_analysis' and run the first cell with this code: import pandas as pd; print(pd.__version__)"
  • "Load the notebook 'model_training.ipynb' and execute all cells."
  • “In the current notebook, add a markdown cell explaining the purpose of each step.”

Tips & gotchas

The agent requires access to an environment with Jupyter Notebook installed. Complex notebooks or computationally intensive tasks may require significant resources and execution time.