agentleFS
wentoraiwentorai/research-plugins/skills/tools/code-exec/SKILL.md

code-exec-skills

Skill298 starsChanged 8 months agoMITView on GitHub

7 code execution skills. Trigger: running code, interactive notebooks, Jupyter, Colab, sandboxed execution. Design: execution environment guides with setup instructions and best practices.

The file

Files
SKILL.md

Code Execution — 7 Skills

Select the skill matching the user's need, then read its SKILL.md.

SkillDescription
google-colab-guideRun and manage Google Colab notebooks for Python and ML research
jupyter-notebook-guideBest practices for computational research notebooks with reproducible workflows
kaggle-api-guideDownload datasets, manage competitions and notebooks via Kaggle API
overleaf-cli-guideSync and manage Overleaf LaTeX projects from the command line
python-reproducibility-guideReproducible Python environments, notebooks, and literate programming
r-reproducibility-guideCreate reproducible research workflows with R and RMarkdown/Quarto
sandbox-execution-guideSecure sandboxed code execution environments for reproducible research computing

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.