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 wanikua · Codex Skill · ★ 2.7k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is danghuangshang safe to install? View the security audit →
English Version 📚 完整文档 🏛️ 当皇上 ✖️ OpenClaw 一行命令起王朝，三省六部皆AI。千里之外调百官，万事不劳御驾亲。 以明朝内阁制为蓝本，用 OpenClaw 框架构建的多 Agent 协作系统。 一台服务器 + OpenClaw = 一支 7×24 在线的 AI 朝廷。 👑 一键登基 一行命令，5 分钟，你就是皇上。 → 快速开始 AI 朝廷是一个开箱即用的多 Agent 协作系统。你是皇帝，AI 是你的大臣——在 Discord 或飞书 @某个 Agent，大臣们就会立刻执行。司礼监接旨、内阁优化 Prompt、六部各
| Stars | 2,701 |
| Forks | 256 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 58.8977483606/100 |
| Open Issues | 37 |
| Last Updated | 2026-05-22 |
| Created | 2026-02-22 |
| Platforms | node |
| Est. Tokens | ~248k |
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danghuangshang is AI 朝廷搭建完整教程 - 从零基础到进阶. It is categorized as a Codex Skill with 2.7k GitHub stars.
danghuangshang is primarily written in TypeScript. It covers topics such as ai, ai-agents, ai-collaboration.
You can find installation instructions and usage details in the danghuangshang GitHub repository at github.com/wanikua/danghuangshang. The project has 2.7k stars and 256 forks, indicating an active community.
danghuangshang is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to danghuangshang on Agent Skills Hub include sre, OpenSwarm, ai-maestro. 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: