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.
npx agentmods add skills/causify-ai/helpers/notebook.split_header_cellsnpx skills add causify-ai/helpers --skill notebook.split_header_cellsgit clone --depth 1 https://github.com/causify-ai/helpersWrote 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.
[](https://agentmods.dev/skills/causify-ai/helpers/notebook.split_header_cells)<a href="https://agentmods.dev/skills/causify-ai/helpers/notebook.split_header_cells"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.split_header_cells.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00408 |
| Opus 5 | $0.00008 | $0.00204 |
| Sonnet 5 | $0.00003 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
notebook.split_header_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 2d 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.
What it actually says
Goal
- Format the markdown cells to match
Workflow
Split Markdown Cells
- Make sure that each markdown cell in a Jupyter notebook contains at most one
header and some text, but not more than one header
- Bad (there are 3 headers in the same cell: one H1, one H2, one H3)
# %% [markdown] # Part 3: Composition Examples ## Example 1: Minimal End-to-End Workflow Rain → Sprinkler → Grass Wet ### Mental Model - Good (each header is in a different cell)
# %% [markdown] # Part 3: Composition Examples # %% [markdown] ## Example 1: Minimal End-to-End Workflow Rain → Sprinkler → Grass Wet # %% [markdown] ### Mental Model - Do not change the content of the markdown text besides splitting cells into multiple ones
- Bad (there are 3 headers in the same cell: one H1, one H2, one H3)
Remove Empty Lines
- Remove empty lines at the beginning or end of a markdown cell
- Bad (there are two headers in the same cell, one H1 and one H2)
# %% [markdown] # Part 3: Composition Examples - Good (each header is in a different cell)
# %% [markdown] # Part 3: Composition Examples
- Bad (there are two headers in the same cell, one H1 and one H2)
Important
- Do not change or remove any Python code cell
- At the end of the transformation, run
jupytext --syncto update the Python paired notebook, following the conventions in# Setup and Initialization→## Utilities vs. Notebook Responsibilitiesin.claude/skills/notebook.rules.md
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.
- 2d ago First seen · 63 lines · 15 tokens per session scan A 43c2bd4f8247
notebook.split_header_cells is a skill published in the GitHub repository causify-ai/helpers (145 stars, last pushed today), licensed Apache-2.0. It adds 15 tokens to every session and 408 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.
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