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 EM-GeekLab · Agent Tool · ★ 89
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is LLMOne safe to install? View the security audit →
LLMOne English 企业级大语言模型部署与服务平台，让大模型真正“开箱即用” 致力于让每个组织和超级个体都能轻松拥有自己的“智能基础设施” 软件下载 用户文档 LLMOne 是一款开源、轻量的 企业级大语言模型部署与服务平台。它致力于解决传统大模型私有化部署中周期长、配置复杂、性能难以保障、运维成本高等痛点。 <img src="
| Stars | 89 |
| Forks | 3 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MulanPSL-2.0 |
| Quality Score | 54.9175474752309/100 |
| Open Issues | 4 |
| Last Updated | 2026-09-21 |
| Created | 2025-03-19 |
| Platforms | node |
| Est. Tokens | ~15k |
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LLMOne is Enterprise-grade LLM automated deployment tool that makes AI servers truly "plug-and-play".. It is categorized as a Agent Tool with 89 GitHub stars.
LLMOne is primarily written in TypeScript. It covers topics such as agent, ai-server, llm.
You can find installation instructions and usage details in the LLMOne GitHub repository at github.com/EM-GeekLab/LLMOne. The project has 89 stars and 3 forks, indicating an active community.
LLMOne is released under the MulanPSL-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to LLMOne on Agent Skills Hub include flama, kaggle-tpu-lab, captain-claw. 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.
Sources & who's responsible: