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Python Packaging Guide

Teaches the agent to structure, build and publish Python packages to PyPI

Source Download skill
Repository
wshobson/agents
Stars
42,095
Licence
MIT
Files
3 files

What it does

Once installed, the agent knows the standard way to set up a Python library or command-line tool: folder layout, a pyproject.toml configuration file, choosing a build backend such as setuptools or hatchling, building wheel and source distributions, and publishing to PyPI or TestPyPI. It gives step-by-step examples and points to reference files for more detailed patterns.

Great for

  • Python developers turning a script or library into an installable package
  • Maintainers preparing a first release to PyPI or a private package index
  • Anyone creating a CLI tool with entry points

Skip it if

  • Non-programmers, since the guidance assumes working knowledge of Python tooling and terminal commands
  • Projects not written in Python, where this guidance does not apply

Try asking

  • “Set up a source-layout Python package with pyproject.toml for my library”
  • “Help me add a command-line entry point to my Python tool and make it installable”
  • “Walk me through building a wheel and publishing my package to TestPyPI first”
Step-by-step guide: how to use Python Packaging GuideInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 3 original files, the MIT licence and an attribution note.

    python-packaging.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip python-packaging.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip python-packaging.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Ask the agent to follow your existing project layout so it does not restructure your code unnecessarily
  • Test with TestPyPI before uploading to the real PyPI, since published versions cannot be overwritten
  • Review any generated pyproject.toml metadata, such as author details and version numbers, before publishing

What's inside

  • references/advanced-patterns.md
  • references/details.md
  • SKILL.md

Redistributed unmodified from wshobson/agents under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.