by tourmind-com
AI agent skills for end-to-end hotel and flight booking—compare live hotel rates across leading OTAs and suppliers, search and verify real-time airfares worldwide, book stays and flights, and manage reservations, hotel cancellations, and payments via the TourMind API.
# Add to your Claude Code skills
git clone https://github.com/tourmind-com/Tourmind-Booking-SkillsGuides for using ai agents skills like Tourmind-Booking-Skills.
Last scanned: 8/8/2026
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"issues": [
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"type": "prompt-injection",
"message": "Possible concealment directive: \"Do not notify the user\"",
"severity": "medium"
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"status": "PASSED",
"scannedAt": "2026-08-08T04:56:34.652Z",
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}See how Tourmind-Booking-Skills compares with popular alternatives.
Tourmind-Booking-Skills is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by tourmind-com. AI agent skills for end-to-end hotel and flight booking—compare live hotel rates across leading OTAs and suppliers, search and verify real-time airfares worldwide, book stays and flights, and manage reservations, hotel cancellations, and payments via the TourMind API. It has 1,248 GitHub stars.
Yes. Tourmind-Booking-Skills passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/tourmind-com/Tourmind-Booking-Skills" and add it to your Claude Code skills directory (see the Installation section above).
Tourmind-Booking-Skills is primarily written in Python. It is open-source under tourmind-com on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Tourmind-Booking-Skills against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Give your AI Agent end-to-end hotel booking and worldwide flight search and booking capabilities. Without leaving your preferred Agent client, you can search global hotel and flight inventory, compare live prices from leading OTAs and suppliers, verify availability and final prices, and use TourMind Booking Skills to complete bookings and payments and check order status.
The examples below show the hotel Skill experience.
TourMind Booking Skills can be used with ChatGPT (Work or Codex mode), Claude Code, WorkBuddy, QClaw, Marvis, OpenClaw, Kimi Work, Doubao Work Mode, Qwen Work Mode, Hermes, Cursor, and other Agent clients that support Skills.
This Skill repository combines hotel and flight support for both personal (ToC) and business (ToB) users. MCP packages use a different structure, so choose the option that matches your use case.
| Integration | Users | Capabilities | Repository |
|---|---|---|---|
| TourMind Booking Skills | ToC and ToB | Hotel and flight Skills | This repository |
| Hotel MCP — Personal (ToC) | ToC | Hotel search and booking for personal users | Hotel Booking AI MCP |
| Hotel MCP — Business (ToB) | ToB | Hotel search and booking for business users | TourMind Booking MCP |
| Flight MCP — Personal and Business | ToC and ToB | One flight MCP shared by personal and business users | Flight Booking AI MCP |
Choose either of the following methods.
Copy and send this message to your Agent:
Please help me install TourMind Booking Skills. Skill repository: git@github.com:tourmind-com/Tourmind-Booking-Skills.git.
npx skills add tourmind-com/tourmind-booking-skills --all
This command installs both Skills—tourmind-booking for hotels and flight-booking-ai for flights—to all detected Agent clients without additional selection prompts.
You can search and compare hotels, and look up airports, without a Token. A Token is required for live flight search and verification, and for any real booking, order, or payment action.
If you already have a TourMind account, you can use its Skill Token. If you do not have an account, sign up for a TourMind account and Token. Send it only to your trusted Agent in a private conversation:
Please use the following TourMind Skill Token when calling the AI Skills:
<YOUR_SKILL_TOKEN>
This Token is only for TourMind AI Skill authentication. Do not expose the complete Token in public conversations, public code repositories, or shared documents.
The Agent will save and configure the Token for the installed Skills. You do not need to create or edit a Token file yourself.
After installation, simply ask the Agent to find a hotel, search for a flight, or plan both together.
Find a hotel in Tokyo for two adults from December 9 to December 13, 2026. We want a twin room near a convenient station, an average price below JPY 18,000 per night, free cancellation, and breakfast if possible. Show me the five best live options with room photos, total stay price, meals, cancellation terms, and the main trade-offs. Do not book yet.
Find round-trip flights from Shanghai to Tokyo for two adults, departing December 9 and returning December 13, 2026. Economy Class, preferably nonstop. Compare the available options by total price, departure and arrival times, airports, connections, duration, and baggage. Show the checked-baggage allowance for each option and highlight any that include at least one checked bag per person. Do not book yet.
Plan a five-day Osaka trip for two people. First compare practical round-trip flights, then find a well-located hotel that fits our dates and budget. Explain the best flight-and-hotel combinations and show the expected flight and hotel costs separately. Let me choose before you book anything.
I like the hotel near Shinjuku Station that you just recommended. Please check which twin rooms are still available, then recheck the best-value option and show me the final price, meals, and cancellation terms. Tell me what information you need from me next and wait for my confirmation before booking.
The morning nonstop flight you just showed me works best. Please recheck its latest total price, then summarize the itinerary and checked-baggage allowance. Tell me which passenger and contact details you need, show me the complete booking summary, and wait for my confirmation before booking it.
Please check the hotel or flight booking we just made and explain its current status. If it can still be paid, show me the available payment methods and final amount first, then wait for my confirmation before continuing.
The Agent handles these steps inside the conversation. You do not need to call APIs or manage local files yourself.
Destination, dates, occupancy, room count, budget and preferences
→ Resolve the location, POI or exact hotel (search_location / keyword search)
→ Search up to 20 candidate hotels (search_hotels)
→ Batch-check live rooms and stay totals (batch_query_room_rates; query_room_rates for one hotel)
→ Rank and show up to five verified hotels
→ Show the selected hotel's details, room images and live room options (get_hotel_detail + room-rate query)
→ Review mandatory fees from the hotel details, then recheck the chosen room's final price, availability and cancellation terms (check_room_availability)
→ If an order action requires authentication, configure the Token; refresh room rates first if the channel changes, then always repeat the final price and availability check with the new Token
→ Provide the guest's full legal name and contact email
→ Show the complete booking summary and wait for explicit confirmation
→ Create the hotel booking (create_booking)
→ Query the booking on request; start payment or cancel an eligible hotel booking only after separate explicit confirmation (query_booking / pay_order / cancel_booking)
The cached candidate price from search_hotels is only an initial signal. User-visible bookable prices co