python-packaging
Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI
Install / Use
npx skills add wshobson/agents --skill python-packagingInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of python-packaging
python-packaging scores 92/100 on our quality scale, 245th of 1,937 Development & Engineering skills we index (top 13%).
Its SKILL.md is 3.6 KB long, well organised into 15 sections with 6 code examples: a solid amount of guidance for an agent.
With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 5 days ago, so python-packaging is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
python-packaging compared with similar skills
All 4 of these similar skills score higher than python-packaging; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| python-packaging (this skill)by wshobson | 92 | 39.9k | 5d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.4k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.8k | today | CLAUDE.md |
| ai-job-searchby MadsLorentzen | 100 | 44.0k | 4d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 6d ago | CLAUDE.md |
Frequently asked questions
- How do I install python-packaging?
- Run
npx skills add wshobson/agents --skill python-packaging. The install tabs above show the steps for each supported agent. - Which AI agents does python-packaging work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is python-packaging safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is python-packaging still maintained?
- The repository was last updated 5 days ago, so python-packaging is actively maintained.
Skill content
View source on GitHubname: python-packaging description: Create distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.
Python Packaging
Comprehensive guide to creating, structuring, and distributing Python packages using modern packaging tools, pyproject.toml, and publishing to PyPI.
When to Use This Skill
- Creating Python libraries for distribution
- Building command-line tools with entry points
- Publishing packages to PyPI or private repositories
- Setting up Python project structure
- Creating installable packages with dependencies
- Building wheels and source distributions
- Versioning and releasing Python packages
- Creating namespace packages
- Implementing package metadata and classifiers
Core Concepts
1. Package Structure
- Source layout:
src/package_name/(recommended) - Flat layout:
package_name/(simpler but less flexible) - Package metadata: pyproject.toml, setup.py, or setup.cfg
- Distribution formats: wheel (.whl) and source distribution (.tar.gz)
2. Modern Packaging Standards
- PEP 517/518: Build system requirements
- PEP 621: Metadata in pyproject.toml
- PEP 660: Editable installs
- pyproject.toml: Single source of configuration
3. Build Backends
- setuptools: Traditional, widely used
- hatchling: Modern, opinionated
- flit: Lightweight, for pure Python
- poetry: Dependency management + packaging
4. Distribution
- PyPI: Python Package Index (public)
- TestPyPI: Testing before production
- Private repositories: JFrog, AWS CodeArtifact, etc.
Quick Start
Minimal Package Structure
my-package/
├── pyproject.toml
├── README.md
├── LICENSE
├── src/
│ └── my_package/
│ ├── __init__.py
│ └── module.py
└── tests/
└── test_module.py
Minimal pyproject.toml
[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"
[project]
name = "my-package"
version = "0.1.0"
description = "A short description"
authors = [{name = "Your Name", email = "you@example.com"}]
readme = "README.md"
requires-python = ">=3.8"
dependencies = [
"requests>=2.28.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0",
"black>=22.0",
]
Package Structure Patterns
Pattern 1: Source Layout (Recommended)
my-package/
├── pyproject.toml
├── README.md
├── LICENSE
├── .gitignore
├── src/
│ └── my_package/
│ ├── __init__.py
│ ├── core.py
│ ├── utils.py
│ └── py.typed # For type hints
├── tests/
│ ├── __init__.py
│ ├── test_core.py
│ └── test_utils.py
└── docs/
└── index.md
Advantages:
- Prevents accidentally importing from source
- Cleaner test imports
- Better isolation
pyproject.toml for source layout:
[tool.setuptools.packages.find]
where = ["src"]
Pattern 2: Flat Layout
my-package/
├── pyproject.toml
├── README.md
├── my_package/
│ ├── __init__.py
│ └── module.py
└── tests/
└── test_module.py
Simpler but:
- Can import package without installing
- Less professional for libraries
Pattern 3: Multi-Package Project
project/
├── pyproject.toml
├── packages/
│ ├── package-a/
│ │ └── src/
│ │ └── package_a/
│ └── package-b/
│ └── src/
│ └── package_b/
└── tests/
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
