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uv

google-deepmind/science-skills · updated Jun 4, 2026

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$npx skills add https://github.com/google-deepmind/science-skills --skill uv
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summary

### Uv

  • name: "uv"
  • description: "Checks whether the uv Python package manager is installed and installs it if missing. Ensures uv is on PATH. Use when another skill requires uv as a prerequisite."
skill.md
name
uv
description
>- Checks whether the uv Python package manager is installed and installs it if missing. Ensures uv is on PATH. Use when another skill requires uv as a prerequisite.

uv (Python Package Manager)

uv is a fast Python package manager used by Science Skills to run their Python CLI scripts. Many skills depend on uv being installed and on PATH.

Ensure uv is available before running any skill that depends on it.

Setup

  1. Check if uv is already available: uv --version If this succeeds, uv is ready — skip the remaining steps.
  2. Check whether uv is installed at its default location but not on PATH: "$HOME/.local/bin/uv" --version If this succeeds, skip to step 4.
  3. If uv is not installed do both these steps in order: (a) Tell the user that uv is a tool for creating a consistent and reliable Python environment used for running the Science Skills, and that you need to install it now. (b) Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh
  4. Add uv to PATH and verify (run as a single command): export PATH="$HOME/.local/bin:$PATH" && uv --version

After setup, bare uv commands should work without repeating the export.

how to use uv

How to use uv on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add uv
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/google-deepmind/science-skills --skill uv

The skills CLI fetches uv from GitHub repository google-deepmind/science-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/uv

Reload or restart Cursor to activate uv. Access the skill through slash commands (e.g., /uv) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.565 reviews
  • Chen Brown· Dec 20, 2024

    Solid pick for teams standardizing on skills: uv is focused, and the summary matches what you get after install.

  • Li Ramirez· Dec 16, 2024

    Useful defaults in uv — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Anika Mehta· Dec 8, 2024

    uv has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 4, 2024

    Keeps context tight: uv is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Anaya Rahman· Nov 27, 2024

    Useful defaults in uv — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Yash Thakker· Nov 23, 2024

    Registry listing for uv matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kwame Haddad· Nov 19, 2024

    uv fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Xiao Agarwal· Nov 11, 2024

    I recommend uv for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chen Chawla· Nov 7, 2024

    uv has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chen Johnson· Oct 26, 2024

    Solid pick for teams standardizing on skills: uv is focused, and the summary matches what you get after install.

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