jupyter

jupyter is a skill for Claude Code from diillson/chatcli. It costs 65 tokens per session (496 once invoked), scanned A, original, Apache-2.0.

A local Python notebook and data-science workflow using Jupyter, an environment for running code alongside notes and results.

In plain words
What is it for?
Running notebooks, analyzing datasets, executing Python cells, and converting notebooks into scripts or reports.
Why use it?
It makes notebook-based analysis repeatable and can produce shareable outputs such as HTML reports.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Running notebooks, analyzing datasets, executing Python cells, and converting notebooks into scripts or reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/diillson/chatcli/jupyter
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add diillson/chatcli --skill jupyter
Clone the repo
git clone --depth 1 https://github.com/diillson/chatcli

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for jupyter

README.md
[![agentmods](https://agentmods.dev/badge/skills/diillson/chatcli/jupyter.svg)](https://agentmods.dev/skills/diillson/chatcli/jupyter)
Your own site
<a href="https://agentmods.dev/skills/diillson/chatcli/jupyter"><img src="https://agentmods.dev/badge/skills/diillson/chatcli/jupyter.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 496 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Excessive Agency · line 52
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.00496
Opus 5 $0.00032 $0.00248
Sonnet 5 $0.00013 $0.00099
Haiku 4.5 $0.00006 $0.00050

Measured 4d ago against content hash f1d00d000429, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

jupyter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

pkg/persona/builtin/skills/jupyter/SKILL.md · 53 lines

What it actually says

Jupyter / Data Science

Local, keyless notebook execution. Detect: command -v jupyter python3 / Get-Command jupyter, python -ErrorAction SilentlyContinue. Install: pipx install jupyter or pip install jupyterlab nbconvert ipykernel.

Execute a notebook headlessly

jupyter nbconvert --to notebook --execute --inplace analysis.ipynb
jupyter nbconvert --to html --execute report.ipynb        # produce a shareable HTML

Read results with @read on the output, or inspect the executed .ipynb cells.

Run ad-hoc Python (no notebook)

For quick analysis, write a .py and run it via @coder exec python3 script.py — manage deps in a venv: python3 -m venv .venv && . .venv/bin/activate && pip install pandas matplotlib.

Convert

jupyter nbconvert --to script notebook.ipynb     # → .py
jupyter nbconvert --to pdf notebook.ipynb         # needs LaTeX (see paper-writing skill)

Live kernel (interactive sessions)

For a persistent kernel across steps, start jupyter console or use jupyter run. Keep the kernel alive only as long as needed; one-shot --execute is simpler for batch work.

Rules

  • Use a project venv; don't pollute the system Python.
  • For plots, save to a file (plt.savefig) and report the path — terminals can't show inline plots.
  • State which packages you installed; never assume pandas/numpy are present without checking.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 53 lines · 65 tokens per session scan A f1d00d000429

Subscribe to this mod's changes

jupyter is a skill published in the GitHub repository diillson/chatcli (90 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 496 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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