301-uv

Initialize Python projects, sync locked environments, and run PEP 723 scripts with uv.

Updated May 21, 2026
One-click install
npx skills add https://github.com/ulf1/trading-regime --skill 301-uv
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 301-uv
Source: https://github.com/ulf1/trading-regime/tree/main/.agent/skills/301-uv
Command: npx skills add https://github.com/ulf1/trading-regime --skill 301-uv

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of slow, non-reproducible Python environment setup by providing a fast workflow to initialize projects, lock dependencies, and run scripts consistently across machines.

Core Features & Use Cases

  • Deterministic Python environments: Sync a local .venv from uv.lock to keep agent and CI runs aligned.
  • PEP 723 inline script dependencies: Execute standalone Python scripts with dependencies declared in-script for easy sharing and automation.
  • Toolchain management: Use uvx for ad-hoc tool runs and uv tool install for persistent tooling.

Quick Start

Initialize a new project with uv using uv init, then run the script file.py that includes PEP 723 dependency metadata with uv run file.py.

Frequently Asked Questions about 301-uv

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

FAQPage Schema
How do I set up a Python environment with uv for deterministic dependency management?

Run standalone Python scripts with inline dependencies using PEP 723 metadata via the uv run file.py command. This allows you to execute shareable scripts with dependencies declared directly in the script.

What is the best way to lock Python dependencies for CI-friendly reproduction?

The best way to lock Python dependencies for CI-friendly reproduction is using uv to generate a uv.lock file. Enforcing local .venv isolation with this lock file keeps agent and CI runs aligned and reproducible.

Can I use uv to manage ad-hoc Python tooling and persistent tools?

Yes, you can use uv to manage ad-hoc Python tooling by running commands with uvx. For persistent tooling installation across your environment, use the uv tool install command.

Why should I use uv for virtual environment management instead of standard Python workflows?

You should use uv for virtual environment management because it solves slow, non-reproducible Python setup by providing a fast workflow. It initializes projects, locks dependencies, and runs scripts consistently across different machines.