An AI-powered skill for automating hotel searches and managing global accommodation data through Booking.com.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install booking-com
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install booking-com using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Booking.com skill is a specialized integration for AI agents that provides programmatic access to one of the world's largest travel platforms. It allows developers to build workflows that interact with over 28 million listings across 220 countries. By utilizing Openclaw Skills, agents can navigate star-rated hotels, apartments, villas, and unique stays like treehouses or houseboats with precision.
This skill is designed to bridge the gap between AI reasoning and the complex logistics of travel planning. It enables autonomous systems to interpret user intent for accommodation and translate it into actionable queries, ensuring high-quality results from the Booking Holdings ecosystem.
To integrate this capability into your AI agent, ensure you have the core framework installed and then add the specific module.
# Install the Openclaw CLI tool
npm install -g @openclaw/cli
# Add the Booking.com skill to your project environment
openclaw install booking-com
The skill organizes accommodation data into a structured format for easy consumption by AI models. Below is the primary metadata taxonomy:
| Field | Type | Description |
|---|---|---|
| property_name | String | The official name of the accommodation |
| location_geo | Object | Latitude and longitude coordinates |
| listing_type | Enum | Hotel, Apartment, Hostel, Villa, etc. |
| pricing_model | Object | Current rate, currency, and tax breakdown |
| cancellation_tag | Boolean | Indicates if free cancellation is available |
| rating_score | Float | Aggregate guest review score (0-10) |
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