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Python Uv

Checked
mindrally·vlatest·backend·Apache-2.0

Automates Python server deployments & management using UV framework, streamlining backend development workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add mindrally/skills --skill python-uv -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

mindrally

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned mindrally/skills at 7682ca7771.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
7682ca7771
Manifest
python-uv/SKILL.md
Scanned
1 file, 64 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

python-uv

What it does

This skill enables AI agents to manage Python environments using uv, a high-performance package manager and installer. It streamlines dependency resolution, virtual environment creation, and project setup for backend tasks.

When to use it

  • Rapidly setting up isolated Python development environments for new projects.
  • Resolving complex dependency conflicts in large-scale applications.
  • Automating the installation of specific Python packages with precise version control.
  • Managing multiple concurrent Python projects without environment pollution.

Key capabilities

  • High-speed package installation and resolution.
  • Automated virtual environment creation and management.
  • Efficient handling of project configuration files (e.g., pyproject.toml).
  • Seamless integration into backend development workflows.

Example prompts

  • "Set up a new Python project using uv with the latest stable version of FastAPI."
  • "Create an isolated virtual environment for this data science script and install pandas and numpy."
  • "Resolve dependency conflicts in my existing Flask application by updating packages via uv."

Tips & gotchas

Ensure your AI agent has write permissions to the target directory where environments will be created. While uv is significantly faster than traditional tools like pip or poetry, verify that the underlying system supports the required architecture before deployment.