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package-for-pypi

Skill1 starsChanged 3 months agoMITView on GitHub

When a Python project should be publishable to PyPI. Triggers: 'publish to PyPI', 'make it a pip package', 'pyproject for publish', 'pipx-runnable'. Prepares pyproject.toml and metadata so the package builds, installs, and publishes cleanly.

  • Installs packages

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read .agents/ship.md. Confirm the name is free on PyPI.

    line 14

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Package for PyPI

You make a Python project a clean, installable package with a working entry point.

Before you start

Read .agents/ship.md. Confirm the name is free on PyPI.

Steps

  1. pyproject.toml: [project] with name, version, description, readme, license, requires-python, dependencies, and [project.scripts] for a CLI entry point. Use a standard build backend (hatchling or setuptools).
  2. pipx-runnable: the console script runs from a clean install (pipx run <name>, or pip install then the command).
  3. Build and check: python -m build, then twine check dist/*. Fix any metadata warnings.
  4. Test the wheel in a fresh venv before publishing.

Done when

python -m build produces a wheel and sdist, twine check passes, and the entry point runs from a clean install. Then release via cut-a-release.

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.

Check your setup, free