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Managing Python Releases

Community
wdm0006
managing-python-releases

Manages Python library releases including semantic versioning, changelog maintenance (Keep a Changelog format), release automation with GitHub Actions, and deprecation workflows. Use when planning releases, writing changelogs, automating release pipelines, or communicating breaking changes.

Overview

Publisherwdm0006
Repositorypython-skills
Skill namemanaging-python-releases
Stars
111
Forks
17
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by wdm0006 on GitHub. Read the source before you install it.

Installation

Install the Managing Python Releases AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/wdm0006/python-skills/tree/main/skills/python/release-management
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/wdm0006/python-skills.git /tmp/python-skills
mkdir -p .claude/skills
cp -r /tmp/python-skills/skills/python/release-management .claude/skills/managing-python-releases
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Managing Python Releases in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Managing Python Releases on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Managing Python Releases is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Python Release Management

Semantic Versioning

MAJOR.MINOR.PATCH (e.g., 1.2.3)

PATCH: Bug fixes, no API changes
MINOR: New features, backward compatible
MAJOR: Breaking changes

Changelog Format (Keep a Changelog)

markdown
# Changelog

## [Unreleased]
### Added
- New `batch_encode()` function

## [1.2.0] - 2024-03-15
### Added
- Support for custom formats (#123)

### Fixed
- Edge case at -180 longitude (#145)

### Deprecated
- `old_function()` - use `new_function()` instead

[Unreleased]: https://github.com/user/repo/compare/v1.2.0...HEAD
[1.2.0]: https://github.com/user/repo/releases/tag/v1.2.0

Categories: Added, Changed, Deprecated, Removed, Fixed, Security

Version in Code

python
# src/package/__init__.py
__version__ = "1.2.3"

# Or use importlib.metadata
from importlib.metadata import version
__version__ = version("my-package")

GitHub Actions Release

A tag-triggered workflow builds with uv and publishes to PyPI via trusted publishing (no stored token). The full canonical pipeline — TestPyPI dry run, GitHub release, and the release runbook — is in AUTOMATION.md.

yaml
# .github/workflows/release.yml
on:
  push:
    tags: ['v*']

jobs:
  release:
    runs-on: ubuntu-latest
    permissions:
      contents: write      # create the GitHub release
      id-token: write      # trusted publishing (no token)
    steps:
      - uses: actions/checkout@v4
      - uses: astral-sh/setup-uv@v5
      - run: uv build
      - uses: softprops/action-gh-release@v2
        with:
          files: dist/*
      - uses: pypa/gh-action-pypi-publish@release/v1

Deprecation Process

Warn with stacklevel=2 so the message points at the caller. Deprecating parameters, classes, or whole modules — and the migration-guide template — is covered in MIGRATION.md.

python
import warnings

def old_function():
    """Deprecated: Use new_function() instead."""
    warnings.warn(
        "old_function() deprecated, will be removed in 2.0.0",
        DeprecationWarning,
        stacklevel=2,
    )
    return new_function()

Release Process

bash
# 1. Update CHANGELOG.md (move Unreleased to version)
# 2. Bump version in pyproject.toml and __init__.py
# 3. Commit and tag
git commit -am "Release v1.2.0"
git tag -a v1.2.0 -m "Release v1.2.0"
git push origin main --tags
# 4. CI publishes automatically

For detailed workflows, see:

Checklist

Before Release:
- [ ] All tests pass
- [ ] CHANGELOG updated
- [ ] Version bumped
- [ ] Documentation current

After Release:
- [ ] PyPI shows new version
- [ ] pip install works
- [ ] GitHub release created
- [ ] Docs updated

Learn More

This skill is based on the Maintenance section of the Guide to Developing High-Quality Python Libraries by Will McGinnis. See these posts for deeper coverage:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Managing Python Releases AI skill do?

Manages Python library releases including semantic versioning, changelog maintenance (Keep a Changelog format), release automation with GitHub Actions, and deprecation workflows. Use when planning releases, writing changelogs, automating release pipelines, or communicating breaking changes.

Why use Managing Python Releases on TypingMind?

Because you install it once and use it with any model. Managing Python Releases is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Managing Python Releases in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/wdm0006/python-skills/tree/main/skills/python/release-management. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Managing Python Releases?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Managing Python Releases?

As many as you like. As long as a model supports skills, you can use Managing Python Releases with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Managing Python Releases AI skill free?

Yes. It is published on GitHub by wdm0006 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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