How do I install the Python Env skill?

Run npx skillmds@latest add flonat/python-env in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Python Env free to use?

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Who published Python Env?

flonat (@flonat) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Python Env by flonat — Agent Skill

Name: Python Env
Rating: 4.666666666666667 (3 reviews)
Author: flonat

Python Env

Create and maintain Python environments and dependencies with uv. Use when installing packages, creating a virtual environment, resolving Python dependency state, or migrating away from pip. Not for general Python coding.

flonat Updated Sep 10, 2026

File contents

Python Environment Management

CRITICAL RULE: Never use pip directly. Always use uv. This applies to all Python package management.

Golden Rule

ALWAYS use uv for Python package and environment management. Never use pip directly.

Commands

Task	Command
Create venv	`uv venv`
Install package	`uv pip install <package>`
Install from requirements	`uv pip install -r requirements.txt`
Run script in project	`uv run python script.py`
Run with dependencies	`uv run --with pandas python script.py`
Install CLI tool globally	`uv tool install <tool>`
Sync project deps	`uv sync`
Add dependency	`uv add <package>`

Project Setup

For new projects:

uv init
uv add <dependencies>
uv sync

For existing projects with pyproject.toml:

uv sync
uv run python main.py

Rules

Never use pip install — always uv pip install or uv add
Never install globally — use uv tool install for CLI tools
Always work in a venv — created by uv venv or uv sync
Use uv run — to execute scripts within the project environment

Typical Project

For a project with a Python entry point:

cd <project>
uv sync                           # Install dependencies
uv run python scripts/task.py     # Run a project script

On [HPC cluster] HPC

Avon uses Miniconda3 + Lmod (not uv) because cluster users need to compose with module load CUDA/12.6.0 and other pre-built modules. The project-specific pattern is hpc/env-setup.sh (conda create + pip install) — see docs/guides/hpc.md and reference implementations under Projects/NLP/{example-project-a,benchmark-gaming-llm-safety}/hpc/env-setup.sh. The local dev env still uses uv; HPC gets its own conda env with identical pins. Don't try to port uv to Avon — the module system assumes conda.

---name: python-envdescription: Create and maintain Python environments and dependencies with uv. Use when installing packages, creating a virtual environment, resolving Python dependency state, or migrating away from pip. Not for general Python coding.---# Python Environment Management**CRITICAL RULE: Never use `pip` directly. Always use `uv`.** This applies to all Python package management.## Golden Rule**ALWAYS use `uv` for Python package and environment management. Never use `pip` directly.**## Commands| Task | Command ||------|---------|| Create venv | `uv venv` || Install package | `uv pip install <package>` || Install from requirements | `uv pip install -r requirements.txt` || Run script in project | `uv run python script.py` || Run with dependencies | `uv run --with pandas python script.py` || Install CLI tool globally | `uv tool install <tool>` || Sync project deps | `uv sync` || Add dependency | `uv add <package>` |## Project SetupFor new projects:```bashuv inituv add <dependencies>uv sync```For existing projects with `pyproject.toml`:```bashuv syncuv run python main.py```## Rules1. **Never use `pip install`** — always `uv pip install` or `uv add`2. **Never install globally** — use `uv tool install` for CLI tools3. **Always work in a venv** — created by `uv venv` or `uv sync`4. **Use `uv run`** — to execute scripts within the project environment## Typical ProjectFor a project with a Python entry point:```bashcd <project>uv sync # Install dependenciesuv run python scripts/task.py # Run a project script```## On [HPC cluster] HPCAvon uses **Miniconda3 + Lmod** (not uv) because cluster users need to compose with `module load CUDA/12.6.0` and other pre-built modules. The project-specific pattern is `hpc/env-setup.sh` (conda create + pip install) — see [`docs/guides/hpc.md`](../../docs/guides/hpc.md) and reference implementations under `Projects/NLP/{example-project-a,benchmark-gaming-llm-safety}/hpc/env-setup.sh`. The local dev env still uses uv; HPC gets its own conda env with identical pins. Don't try to port uv to Avon — the module system assumes conda.

Frequently asked questions