get_bookingLook up a hotel booking by its management token (sent in the confirmation email). Returns the booking status, hotel, dates, and guest details.
| Name | Required | Description | Default |
|---|---|---|---|
| bookingToken | Yes | The booking management token from the confirmation email/URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description does not need to repeat safety. It adds value by detailing the return fields (status, hotel, dates, guest details), aligning with the read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary purpose, no wasted words. Every sentence conveys essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description specifies the returned data types (status, hotel, dates, guest details). It does not cover error cases, but for a lookup tool this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description explains that the bookingToken comes from the confirmation email/URL, adding practical context beyond the schema's definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Look up' and identifies the exact resource 'hotel booking by its management token'. It also lists the returned data (status, hotel, dates, guest details), which distinguishes it from siblings like 'get_my_booking'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the required input (management token from confirmation email). It does not explicitly exclude other scenarios or mention alternatives, but the context is sufficient for correct use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct action or resource: searching, fetching details, checkout flows, booking management, trips, and payment methods. Overlaps like search vs search_hotels and get_booking vs get_my_booking are differentiated by input type or purpose, avoiding ambiguity.
Most tools follow a clear verb_noun pattern (e.g., add_trip_item, create_checkout, get_rooms). A few exceptions like `fetch` and `search` lack a verb prefix, but they are still descriptive and fit the overall convention.
With 18 tools, the server covers the full hotel booking lifecycle without overwhelming complexity. Each tool serves a clear purpose, and the count is well-scoped for the domain.
The tool set covers searching, viewing details, booking, checkout, cancellations, modifications, trips, and payment methods. Minor gaps exist (e.g., no delete_trip or update_payment_method), but the core workflows for booking management are complete.