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 skills add ihatesea69/kiro-kit --skill jupyter-notebooksgit clone --depth 1 https://github.com/ihatesea69/kiro-kitWrote 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/ihatesea69/kiro-kit/jupyter-notebooks)<a href="https://agentmods.dev/skills/ihatesea69/kiro-kit/jupyter-notebooks"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/jupyter-notebooks/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/skills/ihatesea69/kiro-kit/jupyter-notebooks"><img src="https://agentmods.dev/badge/skills/ihatesea69/kiro-kit/jupyter-notebooks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00031 | $0.00332 |
| Opus 5 | $0.00015 | $0.00166 |
| Sonnet 5 | $0.00006 | $0.00066 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
jupyter-notebooks 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 5d 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
Jupyter Notebooks
Activate this skill when working with Jupyter notebooks in data science workflows.
When to Use
- Creating exploratory data analysis notebooks
- Converting notebooks to scripts or reports
- Establishing notebook conventions for teams
- Debugging notebook execution issues
- Setting up JupyterLab environments
Best Practices
- Keep notebooks focused on one analysis question
- Use markdown cells for documentation between code
- Clear outputs before committing to version control
- Extract reusable code into
.pymodules - Number sections for narrative flow
Structure
notebooks/
01-data-exploration.ipynb
02-feature-engineering.ipynb
03-model-training.ipynb
04-evaluation.ipynb
utils/
__init__.py
plotting.py
preprocessing.py
Tools
# Convert to script
jupyter nbconvert --to script notebook.ipynb
# Convert to HTML report
jupyter nbconvert --to html --no-input notebook.ipynb
# Run notebook headless
papermill input.ipynb output.ipynb -p param_name value
Rules
- Never store secrets in notebooks
- Use parameterized notebooks for reproducibility
- Pin library versions in notebook headers
- Keep cell execution order linear (no jumping)
- Use nbstripout to clean outputs before commits
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.
- 5d ago First seen · 61 lines · 31 tokens per session scan A 2e94b4040516
jupyter-notebooks is a skill published in the GitHub repository ihatesea69/kiro-kit (18 stars, last pushed 20d ago), licensed MIT. It adds 31 tokens to every session and 332 once invoked, about $0.0002 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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