Flagged: spawns subprocesses. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by agents-universe · Agent Tool · ★ 530
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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Agents Universe 开源共建 · 技术平权 —— 让智能体像人一样学习和工作。 Agents Universe 是一个开源的企业级 AI Agent 平台。它不是又一个"更聪明的聊天框"，而是要让智能体真正成为能干活的人：入职读懂文档、接任务先规划、以个人身份与权限执行、留下可审计的轨迹——并把这一切沉淀为每个人都能复用、共同建设的资产。 Codex 式三栏界面：左侧会话与项目导航，中间对话流，右侧计划与知识上下文（点击可查看大图） ### 🚀 它正在管理它自己 本项目已部署在 agents-universe.com，并且正在被它自己管理。 平台上的 Product Owner 与 Tech Lead 智能体，就是这个仓库的日常维护者：需求、代码、PR 都由智能体们在对话中完成。 因此——给这个项目做贡献，不需要会写代码。注册账号、配置你自己的模型 API Key 与 Git Token，然后和 Product Owner 聊需求，聊得差不多 @Tech Lead 告诉它要实现哪个，即可完成协作提交 PR。详见 零代码共建。 愿景：技术平权，始于开源 今天，一个智能体好不好用，几乎取决于"是谁调教的"。资深工程师的智能体可以独立交付整个功能，而普通人面对同样的框架，得到的往往是一个"会聊天但干不了活"的助手。智能体的能力被锁在个人的 Prompt 与上下文里：人均而异、无法复制、不可传承。 我们相信，这不应该是一种常态： 开源 —— 平台、技能、工作流、知识全部开放，任何人都可以查看、修改、分发； 共建 —— 经验沉淀为可共享的资产：一个人写好的技能，一万个人可以直接用； 平权 —— 不懂代码的人，也能拥有和资深工程师
| Stars | 530 |
| Forks | 1 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 65.319620496499/100 |
| Open Issues | 1 |
| Last Updated | 2026-10-10 |
| Created | 2026-09-10 |
| Platforms | browser, python |
| Est. Tokens | ~17k |
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agents-universe is 不是问答机器人，而是能真正干活的数字分身。共享智能体，共享项目上下文，让项目所有成员一起协同工作。同时智能体会像人一样通过资料或者工作抽象和总结经验到项目上下文中. It is categorized as a Agent Tool with 530 GitHub stars.
agents-universe is primarily written in Python. It covers topics such as agent, agent-framework, agent-orchestration.
You can find installation instructions and usage details in the agents-universe GitHub repository at github.com/agents-universe/agents-universe. The project has 530 stars and 1 forks, indicating an active community.
agents-universe is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agents-universe on Agent Skills Hub include javis-os, omnicoreagent, ai-agent-tools-catalog. 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: