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.