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Price a Specific Itinerary with Live Fares

fare_quote
Read-only

Get live, bookable-quality fares for one specific itinerary — actual flights, actual prices, for the dates given. Needs a departure date for every flown leg. Use this once the customer has settled on cities and dates and wants real numbers rather than a ballpark; use route_estimate instead when dates are still open. It prices the itinerary as a single fare, so very long or awkward multi-continent trips may come back unpriceable — those genuinely need to be split across separate tickets, which is what AirTreks consultants do by hand.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cabinNoCabin to price. Defaults to economy. 'premium' means premium economy.
datesYesDeparture date for each FLOWN leg, in travel order, as YYYY-MM-DD. Overland legs marked with '000' do not take a date.
adultsNoAdult travellers. Defaults to 1.
citiesYesOrdered list of IATA city/airport codes, e.g. ['LAX','NRT','BKK']. Put '000' between two codes to mark that leg as travelled overland rather than flown.
infantsNoInfants under 2.
childrenNoChildren aged 2-11.
maxOptionsNoHow many fare options to return. Defaults to 5.

TDQS

A4.7/5.0
Behavior4/5

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

With readOnlyHint=true already disclosed, the description adds meaningful behavioral context: every flown leg requires a date, the itinerary is priced as a single fare, and complex multi-continent trips may come back unpriceable. It does not go into failure/response detail, but the annotation plus description gives a clear behavioral picture.

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 front-loaded with the primary purpose, followed by constraint and usage guidance. Every sentence earns its place; it is concise enough while still conveying important edge cases.

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

Completeness5/5

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

Even with no output schema, the description conveys what results to expect ('actual flights, actual prices', 'fare options'), when to invoke it, and when not to. For a tool with 7 parameters and 2 required, this description is sufficient for an agent to select and invoke correctly.

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?

The schema already covers 100% of parameters, so the baseline is 3. The description adds extra meaning by explaining the 'single fare' pricing behaviour and the need for a departure date for every flown leg, which helps interpret the dates and cities arrays beyond their schema descriptions.

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 live, bookable-quality fares') and resource ('one specific itinerary'), and immediately differentiates itself from route_estimate by contrasting 'real numbers' with a 'ballpark'. This makes the tool's scope unmistakable.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('once the customer has settled on cities and dates') and names an alternative (route_estimate) for the open-dates case. It also gives a practical exclusion: very long or awkward multi-continent trips may need to be split, which is actionable guidance.

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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TDQS

A4.1/5.0
Disambiguation3/5

Several tools overlap in the routing/planning space—plan_route, custom_route_build, route_validate, route_suggest, and hub_check all touch alliance feasibility, dead legs, and carrier selection. The descriptions do provide usage cues, but an agent could still struggle to pick the right one for a given step.

Naming Consistency4/5

Most tools follow a clear object-plus-action pattern like route_estimate, route_suggest, fare_product_match, and custom_route_build. plan_route inverts the pattern and itinerary_quote_status is a noun phrase rather than an action, but the overall style is mostly consistent and readable.

Tool Count4/5

Eleven tools is a reasonable scope for a multi-city flight planning domain that spans routing, validation, estimates, quotes, and consultant handoff. The count is not excessive, though some consolidation among the overlapping planning tools would tighten the set.

Completeness4/5

The toolset covers the main journey from trip idea and routing suggestion through validation, fare product matching, live quoting, quote status polling, and human consultant submission. Minor gaps exist—such as no explicit fare rule detail retrieval or date-flexible search—but the core workflow is coherent and has no dead ends.