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get_booking_options

Get booking options and price breakdown for a specific flight by passing its booking token, returning direct links from airlines and OTAs.

Instructions

Get booking links and price breakdown for a specific flight. Pass the booking_token from a search_flights or get_return_flights result. Returns booking options from different airlines/OTAs with direct links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoCountry code
hlNoLanguage code
currencyNoCurrency code
arrival_idYesOriginal arrival airport IATA code
departure_idYesOriginal departure airport IATA code
booking_tokenYesThe booking_token from a flight result to get booking options and deep links
outbound_dateYesOriginal outbound date (YYYY-MM-DD)
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool returns booking options from different airlines/OTAs with direct links, which is useful. However, it does not mention whether the operation is read-only, any side effects, or requirements like the need to pass all original request parameters (departure_id, arrival_id, outbound_date) alongside the token. The description adds some behavioral context but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary purpose, and every sentence earns its place. It clearly states what the tool does, how to use it, and what to expect in return without any filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description explains the high-level return content (booking options from airlines/OTAs with direct links and price breakdown). It covers the essential workflow and expected output. It could mention more about the structure of the returned links or any prerequisites, but for a straightforward retrieval tool it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, giving the baseline of 3. The description adds meaningful context by explaining that booking_token originates from a previous flight search and is used to fetch options. This clarifies the role of the token beyond the schema description. It also hints at why the original parameters are needed, adding value beyond the structured definitions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Get') and a clear resource ('booking links and price breakdown for a specific flight'). It explicitly mentions the required input (booking_token) and distinguishes this tool from siblings like search_flights and get_return_flights, which are flight search tools, not booking-option retrieval tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly instructs when to use this tool: after obtaining a booking_token from search_flights or get_return_flights. It implies the proper workflow without listing exclusions or alternatives, but the context is clear enough. No explicit 'when not to use' is provided, but the usage context is well stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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