SkillX — Agent Tool by zjunlp

by zjunlp · Agent Tool · ★ 106

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About SkillX

👉 SkillX 👈 SkillX: Automatically Constructing Skill Knowledge Bases for Agents 📄arXiv • 𝕏 Blog • 🤗 Huggingface -- Table of Contents 👀Overview 🔧Installation 🏃Quick Start 🎁Acknowledgement 🚩Citation 📖 Overview SkillX is a fully automated framework that constructs a reusable, plug-and-play skill knowledge base for LLM agents from experience. Instead of storing raw trajectories, workflows, or loosely structured reflections, SkillX distills agent experience into a three-level skill hierarchy: Planning Skills for high-level task organization Functional Skills for reusable tool-based subroutines Atomic Skills for execution-oriented tool usage patterns Built with a strong backbone agent, SkillX produces a transferable skill library that can be directly plugged into weaker base agents and new environm

agent-skillsagentic-aiartificial-intelligencelarge-language-modelsnatural-language-processingskillsskillx

Quick Facts

Stars106
Forks9
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score65.471586462705/100
Open Issues2
Last Updated2026-04-30
Created2026-01-09
Platformspython
Est. Tokens~84k

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Frequently Asked Questions

What is SkillX?

SkillX is SkillX: Automatically Constructing Skill Knowledge Bases for Agents. It is categorized as a Agent Tool with 106 GitHub stars.

What programming language is SkillX written in?

SkillX is primarily written in Python. It covers topics such as agent-skills, agentic-ai, artificial-intelligence.

How do I install or use SkillX?

You can find installation instructions and usage details in the SkillX GitHub repository at github.com/zjunlp/SkillX. The project has 106 stars and 9 forks, indicating an active community.

What license does SkillX use?

SkillX is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to SkillX?

The top alternatives to SkillX on Agent Skills Hub include anchoring-ai, dialop, pgmcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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