SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/benchflow-ai/skillsbenchnpx agentmods add skills/benchflow-ai/skillsbench/uv-package-managerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/benchflow-ai/skillsbench/uv-package-manager)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/uv-package-manager"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/uv-package-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/uv-package-manager"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/uv-package-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.04172 |
| Opus 5 | $0.00021 | $0.02086 |
| Sonnet 5 | $0.00008 | $0.00834 |
| Haiku 4.5 | $0.00004 | $0.00417 |
Grade C, and why
uv-package-manager scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
curl -LsSf https://astral.sh/uv/install.sh | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -LsSf https://astral.sh/uv/install.sh | sh This is a copy
100% identical to uv-package-manager — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 832 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UV Package Manager
Comprehensive guide to using uv, an extremely fast Python package installer and resolver written in Rust, for modern Python project management and dependency workflows.
When to Use This Skill
- Setting up new Python projects quickly
- Managing Python dependencies faster than pip
- Creating and managing virtual environments
- Installing Python interpreters
- Resolving dependency conflicts efficiently
- Migrating from pip/pip-tools/poetry
- Speeding up CI/CD pipelines
- Managing monorepo Python projects
- Working with lockfiles for reproducible builds
- Optimizing Docker builds with Python dependencies
Core Concepts
1. What is uv?
- Ultra-fast package installer: 10-100x faster than pip
- Written in Rust: Leverages Rust's performance
- Drop-in pip replacement: Compatible with pip workflows
- Virtual environment manager: Create and manage venvs
- Python installer: Download and manage Python versions
- Resolver: Advanced dependency resolution
- Lockfile support: Reproducible installations
2. Key Features
- Blazing fast installation speeds
- Disk space efficient with global cache
- Compatible with pip, pip-tools, poetry
- Comprehensive dependency resolution
- Cross-platform support (Linux, macOS, Windows)
- No Python required for installation
- Built-in virtual environment support
3. UV vs Traditional Tools
- vs pip: 10-100x faster, better resolver
- vs pip-tools: Faster, simpler, better UX
- vs poetry: Faster, less opinionated, lighter
- vs conda: Faster, Python-focused
Installation
Quick Install
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# Using pip (if you already have Python)
pip install uv
# Using Homebrew (macOS)
brew install uv
# Using cargo (if you have Rust)
cargo install --git https://github.com/astral-sh/uv uv
Verify Installation
uv --version
# uv 0.x.x
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 832 lines · 42 tokens per session scan C 85c71e75e639
uv-package-manager is a skill published in the GitHub repository benchflow-ai/skillsbench (1,764 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 4,172 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). It is 100% identical to uv-package-manager, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
uv-package-manager
Master the uv package manager for fast Python dependency management, virtual environments, and modern Python project workflows. Use when setting up Python projects, managing dependencies, or optimizing Python development workflows with uv.
simple-modern-uv
Start, selectively modernize, fully migrate, or update Python projects using simple-modern-uv practices: uv, ruff, BasedPyright, pytest, GitHub Actions CI, and tag-driven PyPI publishing. Use when creating a Python project; adding selected tooling or repository practices to an existing project; migrating from Poetry…
pypi-ops
Publish Python packages to PyPI via OIDC Trusted Publishing (PEP 740 attestations, gh-action-pypi-publish) instead of stored tokens. Use for: invalid-publisher errors, pending-publisher 404s, uv publish/twine, TestPyPI, environment approval gates, and rotating/auditing publish tokens.
python-deploy
Build and deploy Python applications — uv, poetry, pdm, pipenv, pip, framework detection, and Dockerfile patterns. Use when deploying a Python project, or when requirements.txt, pyproject.toml, or Pipfile is detected.
plate-tectonics-geospatial
Analyze plate tectonics data using GeoPandas, identify points within plates, and calculate distances to boundaries.
python-csv-generation
Generate structured CSV files from Python data using the csv module for tabular data export.