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 megumi-ben · Agent Tool · ★ 200
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is marco-polo.skill safe to install? View the security audit →
https://github.com/user-attachments/assets/ff0209ed-4060-4cf2-8acd-9d37f2ab72ae 🧭 Marco Polo English | 简体中文 Your next trip, mapped out. An open-source AI travel assistant that turns your preferences into a trip you can actually follow. Choose your stay and sights. Marco Polo connects real locations, transport, visiting hours, and reservations—then delivers an interactive map, food guide, and city guide in one travel handbook. Explore the live demo · Get started · Watch the video · Contribute Click to explore the Nanjing handbook · No setup needed · Demo content is in Chinese.Screenshot: original Amap version. Public demo: OpenFreeMap. Lines show visit order; transport
| Stars | 200 |
| Forks | 6 |
| Language | HTML |
| Category | Agent Tool |
| Quality Score | 65.0691967952806/100 |
| Last Updated | 2026-10-09 |
| Created | 2026-06-30 |
| Est. Tokens | ~20k |
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marco-polo.skill is AI travel planning skill · 旅行攻略助手 | Real routes, reservation checklists & interactive travel handbooks.. It is categorized as a Agent Tool with 200 GitHub stars.
marco-polo.skill is primarily written in HTML. It covers topics such as agent-skills, ai-travel, amap.
You can find installation instructions and usage details in the marco-polo.skill GitHub repository at github.com/megumi-ben/marco-polo.skill. The project has 200 stars and 6 forks, indicating an active community.
The top alternatives to marco-polo.skill on Agent Skills Hub include TripStar-Java, JourniOne-Planning-Skills, jianhao-travel-planner. 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: