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Scaffold and upgrade Python projects with docs, CI/CD, Docker, and more.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "io.github.KaiErikNiermann/pypreset" yet — see the docs or source repo.
Create a new Python CLI project scaffold with a src layout, pytest, ruff, mypy, and pyproject.toml. Generate the base directory structure and sample code.
A complete project scaffold, configuration files, and starter code ready for development.
Analyze the current repository and add GitHub Actions CI, pre-commit, Sphinx documentation setup, and a Dockerfile to this Python project while preserving the existing structure as much as possible.
CI/CD, documentation, and containerization files added to the existing project with minimal structural disruption.
Turn this Python library into a template ready for open-source release by adding a README, license, contribution guide, release workflow, and basic test setup.
A standardized set of project files and workflow configurations suitable for open-source release and continuous delivery.
Standardize and serve structured project context to AI coding assistants.
Analyze Python scientific codebases with architecture, dependencies, tests, and AI-ready context.
Helps AI agents scaffold, preview, and write project starters.
Let AI run Python, manage files and packages, and automate technical tasks.
Search Pydantic and Pydantic AI docs locally with BM25.
Get context-aware docs, types, and examples for any npm package.