notebook.split_cells

notebook.split_cells is a skill for Claude Code from causify-ai/helpers. It costs 13 tokens per session (142 once invoked), scanned A, original, Apache-2.0.

A notebook-editing guide that separates a Jupyter notebook into cells with one logical task each. Jupyter notebooks combine executable code with explanatory text.

In plain words
What is it for?
Reorganizing notebooks and keeping their paired Python files synchronized with Jupytext, a tool that links notebooks and text-based Python files.
Why use it?
It prevents cells from becoming difficult to understand, reuse, or debug by mixing several unrelated steps.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; reads .claude/ paths.

Good fit Reorganizing notebooks and keeping their paired Python files synchronized with Jupytext, a tool that links notebooks and text-based Python files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/causify-ai/helpers/notebook.split_cells
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 causify-ai/helpers --skill notebook.split_cells
Clone the repo
git clone --depth 1 https://github.com/causify-ai/helpers

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 notebook.split_cells

README.md
[![agentmods](https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.split_cells/github.svg)](https://agentmods.dev/skills/causify-ai/helpers/notebook.split_cells)
Your own site
<a href="https://agentmods.dev/skills/causify-ai/helpers/notebook.split_cells"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.split_cells/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for notebook.split_cells

Your own site · 80×15
<a href="https://agentmods.dev/skills/causify-ai/helpers/notebook.split_cells"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.split_cells.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 142 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 3
    Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.
    Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 $0.00013 $0.00142
Opus 5 $0.00006 $0.00071
Sonnet 5 $0.00003 $0.00028
Haiku 4.5 $0.00001 $0.00014

Measured 7d ago against content hash 53a32d5ddb63, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

notebook.split_cells 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 7d 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.

.claude/skills/notebook.split_cells/SKILL.md · 19 lines

What it actually says

Goal

  • Make sure that each code cell in a Jupyter notebook performs only one logical task

Conventions

  • Implement the rules in .claude/skills/notebook.rules.md under
    • ## Single Responsibility Per Cell and
    • ## Split Cells That Perform Distinct Steps

Sync

  • At the end, sync the paired .py file with Jupytext following the conventions in # Setup and Initialization## Utilities vs. Notebook Responsibilities in .claude/skills/notebook.rules.md
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. 7d ago First seen · 19 lines · 13 tokens per session scan A 53a32d5ddb63

Subscribe to this mod's changes

notebook.split_cells is a skill published in the GitHub repository causify-ai/helpers (145 stars, last pushed yesterday), licensed Apache-2.0. It adds 13 tokens to every session and 142 once invoked, about $0.0001 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.