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Grok Bot+18 agentsCitable Python Packages from Research Code
Turn research scripts into a pip-installable, citable Python package: src/ layout with uv, ruff and pytest, CITATION.cff and a How to cite section, a lock file for reproducibility, and your code moved without rewrites.
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Citable Python Packages from Research Code
Example session with this skill installed
Turn my two analysis scripts, fit_arrhenius.py and read_runs.py, into a pip-installable package I can cite in my thesis. There's a small example dataset in data/rates.csv. Author: Alex Rivera (ORCID 0000-0002-1825-0097), MIT licence, no paper yet. I'd like an examples folder. Go ahead without waiting for my confirmation, run the tests at the end, and flag anything in my code you'd change instead of changing it.
- Read your context and instructions
- Compiled the citable python packages
Package arrhenius-fit (import arrhenius_fit), built from the two scripts:
src/arrhenius_fit/: both scripts, unchanged except one import made relative; functions re-exported from__init__.pypyproject.toml(hatchling, numpy>=1.24, matplotlib>=3.7, dev group with pytest, ruff, pyyaml),uv.lock,.python-versionCITATION.cffwith the ORCID,LICENSE(MIT),README.mdwith quick start and "How to cite" (BibTeX)examples/01_fit_example_data.py(prints Ea = 52.7 ± 0.5 kJ/mol, saves a plot) and a test that runs it
Checks: uv run pytest: 10 passed. uv build: wheel and sdist built. Ruff findings only in the two moved files, left for you.
Flagged, not changed
min_replicatescounts usable rows, not replicates per temperaturefit_arrheniusfails on plain lists (1.0 / T)- hard-coded cluster path in the
__main__block - matplotlib is a required dependency only because of the plot in
__main__
Still to do: repository URL placeholder, no DOI yet, git init, PyPI not configured.
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About this skill
What it does
Your agent turns loose research code, or just an idea, into a Python package other people can install, run and cite. It:
- Builds a clean package with a fixed, modern toolchain:
uvfor the environment and lock file,hatchlingto build,ruffto lint,pytestto test, and asrc/layout so tests run against the installed package. - Makes it citable: a
CITATION.cff(authors, ORCID iDs, licence, version), a README with a "How to cite" section and BibTeX, and a test that fails if the citation is invalid, still has placeholders, or drifts from the package version. - Records what your results ran on: lower bounds in
pyproject.toml, exact versions in a committeduv.lock, the Python version in.python-version. - Keeps your code yours: existing scripts are copied into the package verbatim and the originals are left in place. The only edit is turning imports between your own scripts into package imports. Code that runs on import, hard-coded paths, undeclared imports and lint findings are flagged for you to decide, never silently rewritten.
- Runs the checks (
uv sync,ruff,pytest) and hands over the exact commands plus a list of what is still a placeholder.
Optional extras
On request: an examples/ folder with a test that runs every example, a notebooks/ folder, a GitHub Actions CI workflow testing the oldest and newest Python, and a Dockerfile that installs the locked versions. When you want a DOI, it prepares the release and gives you a checklist for Zenodo's GitHub integration, with a Code availability statement for your paper.
What's included
SKILL.md: the workflow for both starting points (an idea, or existing scripts)references/: annotated templates forpyproject.toml,CITATION.cffand its test, the README, CI, Docker and examples, plus guides to reproducibility and releases with a DOI
Part of the Aurora Lab research pipeline
Works entirely on its own. If you keep a research/ folder, it can read research/refs.bib and research/paper/ to fill in the paper citation. No skill calls another.
How to use
Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.
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Requires
Python
uv (Python tool runner)
Git