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 LeeFly-cn · Agent Tool · ★ 55
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is TripStar-Java safe to install? View the security audit →
TripStar 基于 Spring Boot 4 与 Spring AI Alibaba 的多智能体旅行规划系统 TripStar 是一个前后端分离的 AI 旅行规划项目。系统使用多 Agent 协作理解用户需求，读取小红书旅行内容，查询高德 POI、天气、酒店与餐饮，并生成包含每日路线、地图、景点图片、预算和知识图谱的完整攻略。 后端 GitHub：LeeFly-cn/TripStar-Java 后端 Gitee：haigoyaadmin/trip-star-java 前端 GitHub：LeeFly-cn/TripStar-Frontend 社区：LinuxDo 项目预览 双模式规划入口 行程概览 每日行程 <a href="docs/images/daily-i
| Stars | 55 |
| Forks | 14 |
| Language | JavaScript |
| Category | Agent Tool |
| License | GPL-2.0 |
| Quality Score | 54.8546981242714/100 |
| Last Updated | 2026-07-20 |
| Created | 2026-07-06 |
| Platforms | node |
| Est. Tokens | ~13k |
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TripStar-Java is TripStar Java 实现版：基于 Spring Boot 4 + Spring AI Alibaba StateGraph/ReactAgent 的 AI 旅行规划后端，支持高德 Tool、小红书内容接入、Structured Output 和 Agent Trace。. It is categorized as a Agent Tool with 55 GitHub stars.
TripStar-Java is primarily written in JavaScript. It covers topics such as ai-agent, amap, java.
You can find installation instructions and usage details in the TripStar-Java GitHub repository at github.com/LeeFly-cn/TripStar-Java. The project has 55 stars and 14 forks, indicating an active community.
TripStar-Java is released under the GPL-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to TripStar-Java on Agent Skills Hub include marco-polo.skill, api2mcp4j, mcp-zap-server. 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: