modern-python-substrate

Automate setup of modern Python toolchains with uv, ruff, ty, and pytest.

31|20|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/mycelium-hq/ai-brain-starter --skill modern-python-substrate
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: modern-python-substrate
Source: https://github.com/mycelium-hq/ai-brain-starter/tree/main/skills/modern-python-substrate
Command: npx skills add https://github.com/mycelium-hq/ai-brain-starter --skill modern-python-substrate

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the setup of a modern Python toolchain (uv, ruff, ty, pytest, and standard src/ layout) for new or migrating Python projects.

Core Features & Use Cases

  • uv-based installation and venv management for Python 3.11+ on Linux/macOS, with Windows parity where relevant.
  • Ruff for linting/formatting, Ty for type checking, Pytest for tests, and Hypothesis for property-based testing; enforces a canonical src/ layout and a pyproject.toml as the single source of truth.
  • Use cases include starting a new Python project, migrating from legacy toolchains to uv+tools, and aligning with LLM-stack patterns when integrating with SDKs like Anthropic/OpenAI/tiktoken.

Quick Start

Initialize a new Python project with the substrate to bootstrap a complete toolchain and project layout.

Frequently Asked Questions about modern-python-substrate

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a modern Python toolchain with uv and ruff for a new project?

Setting up a modern Python toolchain with uv and ruff involves bootstrapping a project that includes uv for venv management, ruff for linting, ty for type checking, and pytest, all unified within a single pyproject.toml file.

What is the standard way to structure a Python project using uv and pyproject.toml?

The standard way to structure a Python project using uv is implementing a canonical src/ layout, where pyproject.toml serves as the single source of truth for dependencies, formatting rules, and testing configurations.

Can I migrate an existing Python project to a uv-based workflow without breaking dependencies?

You can migrate legacy Python projects to a uv-based workflow by transitioning dependency management and virtual environment creation to uv, while standardizing the configuration under a unified pyproject.toml to maintain existing dependencies.

Does the uv and ruff Python toolchain support Windows, or is it limited to Linux and macOS?

The uv and ruff Python toolchain primarily targets Python 3.11+ on Linux and macOS, but it maintains Windows parity where relevant, ensuring cross-platform compatibility for development workflows.

How do I configure pytest and Hypothesis for property-based testing in a modern Python project?

Configuring pytest and Hypothesis for property-based testing is handled by bootstrapping the project with a standard pyproject.toml, which integrates both testing frameworks into the modern Python workflow automatically.

When should I not use uv for Python dependency management instead of traditional tools?

You should evaluate not using uv for Python dependency management if your project requires legacy Python versions below 3.11, or if your team environment cannot adopt a unified pyproject.toml configuration approach.