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 RollingGo-AI · MCP Server · ★ 147
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rollinggo-hotel-skill-cn safe to install? View the security audit →
RollingGo全球酒店预订Skill-2.0新版本 English | 简体中文 Search → Recommend → Price Confirm → Book → Orders Check 只需对 Agent 说一句「我要去 XX 玩，帮我订酒店」 RollingGo酒店预订Skill就能帮你全程搞定： 🔍 按需求智能筛选，省心帮你挑酒店 📋 实时查房型、报价和退改规则，明明白白不踩坑 🛏️ 心仪房型提前锁定，不用愁晚订没房 🔐 无需切换其他平台，Agent内一键安全登录，隐私信息有保障 💳 说句“帮我下单”就跳转支付页面
| Stars | 147 |
| Forks | 1 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 66.5138963890409/100 |
| Last Updated | 2026-08-28 |
| Created | 2026-06-10 |
| Platforms | claude-code, cli, codex, mcp, python |
| Est. Tokens | ~14k |
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rollinggo-hotel-skill-cn is 全球酒店预订&低价监控提醒Skill，200万+精选酒店，独家优惠价格，让你的Agent轻松预订品质酒店，支持支付宝下单+查询历史订单，24 小时客服支持，全天候响应。. It is categorized as a MCP Server with 147 GitHub stars.
rollinggo-hotel-skill-cn is primarily written in Python. It covers topics such as agent-skill, agent-toolkit, ai-agents.
You can find installation instructions and usage details in the rollinggo-hotel-skill-cn GitHub repository at github.com/RollingGo-AI/rollinggo-hotel-skill-cn. The project has 147 stars and 1 forks, indicating an active community.
rollinggo-hotel-skill-cn is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to rollinggo-hotel-skill-cn on Agent Skills Hub include awesome-ai-agent-skills, Claude-Skills, ai-agent-team. 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: