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 tourmind-com · Codex Skill · ★ 1.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Tourmind-Booking-Skills safe to install? View the security audit →
TourMind Booking Skills Let Your Agent Book Hotels Worldwide Bring Your Customers Into Intelligent Travel Product Page | Live Demo | Company English | 简体中文 | 日本語 | Español Turn any AI agent into an end-to-end hotel booking assistant—search global inventory, compare live rates across leading OTAs and hotel suppliers, verify availability, and complete booking, payment, cancellation, and order management in one convers
| Stars | 1,040 |
| Forks | 187 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 74.5734530520368/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-09 |
| Created | 2026-07-13 |
| Platforms | codex, python |
| Est. Tokens | ~16k |
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Tourmind-Booking-Skills is AI agent skill for end-to-end hotel search and booking—compare live rates across leading OTAs and hotel suppliers, verify availability, book stays, and manage reservations, cancellations, and payments. It is categorized as a Codex Skill with 1.0k GitHub stars.
Tourmind-Booking-Skills is primarily written in Python. It covers topics such as agent-skills, ai-agent, booking-api.
You can find installation instructions and usage details in the Tourmind-Booking-Skills GitHub repository at github.com/tourmind-com/Tourmind-Booking-Skills. The project has 1.0k stars and 187 forks, indicating an active community.
Tourmind-Booking-Skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Tourmind-Booking-Skills on Agent Skills Hub include LetsFG, babysitter, getspecstory. 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: