No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zjunlp · Agent Tool · ★ 284
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is SkillX safe to install? View the security audit →
👉 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
| Stars | 284 |
| Forks | 26 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.471586462705/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-03 |
| Created | 2026-01-09 |
| Platforms | python |
| Est. Tokens | ~15k |
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SkillX is SkillX: Automatically Constructing Skill Knowledge Bases for Agents. It is categorized as a Agent Tool with 284 GitHub stars.
SkillX is primarily written in Python. It covers topics such as agent-skills, agentic-ai, artificial-intelligence.
You can find installation instructions and usage details in the SkillX GitHub repository at github.com/zjunlp/SkillX. The project has 284 stars and 26 forks, indicating an active community.
SkillX is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to SkillX on Agent Skills Hub include minecraft-mcp-server, anchoring-ai, dialop. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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