AgentSkills: A Curated Collection for LLM Agent Skills and Resources

Introduction

The scienceaix/agentskills repository is an "Awesome List" dedicated to the rapidly evolving field of skills for large language models (LLMs). It provides a meticulously curated collection of resources, including academic papers, development tools, open-source projects, and frameworks. The repository aims to be a comprehensive guide for anyone interested in building, composing, and deploying specialized skills for LLM-powered agents, covering everything from core ecosystems like Anthropic Skills and the Model Context Protocol (MCP) to advanced research in tool use and computer interaction.

How to Explore

As an "Awesome List," agentskills does not require traditional installation. Instead, users can explore its rich content directly on GitHub. The repository's README.md is structured with a detailed table of contents, allowing for easy navigation through various sections. You can delve into specific areas such as:

Anthropic Skills, Core Ecosystem: Official announcements, documentation, and GitHub repositories related to Anthropic's skill system.
Model Context Protocol (MCP): Specifications, SDKs, and community resources for this open standard connecting AI to data sources.
Academic Papers: A categorized list of research on skill learning, tool use, computer use, web agents, and multi-agent collaboration.
Open-Source Projects & Frameworks: A directory of popular agent frameworks, browser automation tools, and coding agents.
Benchmarks & Evaluation: Resources for assessing LLM agent performance across various tasks.
Tutorials & Educational Resources: Guides from official sources and the community to help you get started.

Simply click on the section headers in the README to jump to the relevant content.

Key Highlights

The agentskills repository stands out by offering a structured overview of a complex domain. Some key highlights include:

Anthropic's Ecosystem: Direct links to official Anthropic resources, including their skills repository (62k+ stars), claude-code (42k+ stars), and comprehensive guides on building skills for Claude.
Model Context Protocol (MCP): Detailed information on MCP, an open standard for connecting AI to data sources, including its donation to the Agentic AI Foundation and various SDKs (Python, TypeScript, Go, C#).
Cutting-Edge Research: A vast collection of academic papers, categorized for easy access, covering topics like SAGE for self-improving agents, CUA-Skill for computer-using agents, and UI-TARS for automated GUI interaction.
Practical Open-Source Tools: A curated list of widely used agent frameworks such as LangGraph, Microsoft AutoGen, CrewAI, and Semantic Kernel, alongside browser automation tools like browser-use and Skyvern, and coding agents like OpenHands and Aider.
Comprehensive Benchmarking: Links to critical benchmarks like SWE-bench, GAIA, Berkeley Function Calling Leaderboard (BFCL), and OSWorld, providing insights into agent performance and evaluation methodologies.

Why Use AgentSkills?

For developers, researchers, and enthusiasts in the AI space, agentskills offers an unparalleled resource for staying current with LLM agent capabilities. It consolidates scattered information into a single, navigable hub, saving significant time in discovering relevant papers, tools, and best practices. Whether you are looking to understand the foundational concepts of agent skills, implement advanced tool use, or explore the latest open-source frameworks, this repository provides a clear roadmap and direct access to the most important developments in the field. Its focus on a rapidly evolving area makes it an essential bookmark for anyone serious about building the next generation of intelligent agents.