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.
git clone --depth 1 https://github.com/langfuse/langfuse-docsWrote 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/rules/langfuse/langfuse-docs/ipynb-files)<a href="https://agentmods.dev/rules/langfuse/langfuse-docs/ipynb-files"><img src="https://agentmods.dev/badge/rules/langfuse/langfuse-docs/ipynb-files/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.
<a href="https://agentmods.dev/rules/langfuse/langfuse-docs/ipynb-files"><img src="https://agentmods.dev/badge/rules/langfuse/langfuse-docs/ipynb-files.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.00442 |
| Opus 5.5 | $0.00000 | $0.00177 |
| Sonnet 5.5 | $0.00000 | $0.00088 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
ipynb-files 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 1mo 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
Cursor Rules for Handling Jupyter Notebooks
Overview
This file contains rules and prompts for handling Jupyter Notebook (.ipynb) files in Cursor IDE, which currently doesn't have native support for .ipynb files.
System Rules
-
When a user requests to create or edit a .ipynb file:
- Use template.py as the base for generating the notebook
- Create a Python file that uses the template functions to generate the desired notebook
- Execute the Python file to generate the .ipynb file
-
For notebook creation:
- Create a new Python file using the template functions
- Define the notebook structure using add_markdown_cell() and add_code_cell()
- Use save_notebook() to generate the .ipynb file
-
For notebook editing:
- Load the existing .ipynb file using load_notebook()
- Make the requested modifications
- Save the updated notebook using save_notebook()
-
For notebook to Python conversion:
- Use notebook_to_python() function to convert .ipynb to .py
- This is useful for version control and editing in Cursor
Example Prompts
-
Creating a new notebook: "Please create a new Jupyter notebook with a markdown cell explaining the project and a code cell with a simple plot."
-
Editing an existing notebook: "Please modify the existing notebook to add a new code cell that performs data analysis."
-
Converting a notebook: "Please convert this notebook to a Python file so I can edit it in Cursor."
Implementation Notes
- Always use the template.py functions for notebook manipulation
- Keep the Python file and .ipynb file in sync
- Use proper error handling when working with files
- Maintain consistent formatting in the generated notebooks
Best Practices
- Document all notebook cells with clear markdown explanations
- Use proper code organization in code cells
- Include necessary imports at the beginning of the notebook
- Save intermediate results when working with large datasets
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.
- 1mo ago First seen · 55 lines · 0 tokens per session scan A e6e0222c8eb5
ipynb-files is a cursor rule published in the GitHub repository langfuse/langfuse-docs (246 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 442 tokens. 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 2026-08-30.
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