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 kclemoveki/agentic-skills-eda --skill execute-notebookgit clone --depth 1 https://github.com/kclemoveki/agentic-skills-edaWrote 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/kclemoveki/agentic-skills-eda/execute-notebook)<a href="https://agentmods.dev/skills/kclemoveki/agentic-skills-eda/execute-notebook"><img src="https://agentmods.dev/badge/skills/kclemoveki/agentic-skills-eda/execute-notebook/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/kclemoveki/agentic-skills-eda/execute-notebook"><img src="https://agentmods.dev/badge/skills/kclemoveki/agentic-skills-eda/execute-notebook.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 | $0.00047 | $0.01171 |
| Opus 5.5 | $0.00019 | $0.00468 |
| Sonnet 5.5 | $0.00009 | $0.00234 |
| Haiku 4.5 | $0.00005 | $0.00117 |
Grade A, and why
execute-notebook 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Execute Notebook
Run the notebook at $ARGUMENTS end-to-end with a fresh kernel and persist its outputs back into the file. This is the "restart and run all" hygiene step recommended by Rule 7 of Ten Simple Rules for Writing and Sharing Computational Analyses in Jupyter Notebooks (Rule et al. 2019), automated.
Step 1 — Pre-flight checks
Before invoking papermill, verify:
- Notebook exists: resolve
$ARGUMENTSto an absolute path. If the file does not exist, fail with:Notebook not found: <path>. - Papermill installed: run
python3 -c "import papermill"viaBash. If it raisesModuleNotFoundError, fail with:papermill not installed. Install with one of: pip install papermill poetry add papermill - Dependencies sanity check (warning, not error): if neither
requirements.txtnorpyproject.tomlexists in the notebook's directory or cwd, print:
Do not abort on this warning — proceed with execution.WARNING: no requirements.txt or pyproject.toml found. Consider running /freeze-deps first. - Kernel availability: read the notebook JSON, extract
metadata.kernelspec.name. Runjupyter kernelspec list --jsonviaBashand verify the kernel exists. If not, fail with:Kernel '<name>' not available. Available kernels: <output of jupyter kernelspec list>
Step 2 — Execute the notebook
Invoke papermill from the notebook's directory as cwd (so relative paths like data/foo.csv resolve correctly):
cd <notebook_dir>
python3 -c "
import papermill as pm
import time
start = time.time()
try:
pm.execute_notebook(
input_path='<notebook_filename>',
output_path='<notebook_filename>', # overwrite
kernel_name='<kernel_from_metadata>',
progress_bar=False,
log_output=False,
request_save_on_cell_execute=True, # save partial output on failure
)
print(f'OK {time.time() - start:.1f}')
except pm.PapermillExecutionError as exc:
print(f'FAIL {time.time() - start:.1f} cell={exc.cell_index} ename={exc.ename} evalue={exc.evalue}')
raise
"
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.
- 2mo ago First seen · 117 lines · 47 tokens per session scan A 9a228b3a4923
execute-notebook is a skill published in the GitHub repository kclemoveki/agentic-skills-eda (2 stars, last pushed 5mo ago), licensed MIT. It adds 47 tokens to every session and 1,171 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
execute-notebook compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| execute-notebookkclemoveki/agentic-skills-eda | Skill | 2 | 5mo ago | MIT | A | 47 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 3d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |