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plan_multi_stop_trip

Plan multi-leg itineraries for holidays by searching each leg in parallel. Automatically resolves each stop to nearby airports and shows the cheapest flight per leg with alternatives.

Instructions

Plan a multi-leg trip by searching each leg in parallel. Ideal for internal/domestic routing within a multi-country holiday: "I'll be in Buenos Aires on Oct 17, want to visit Patagonia on Oct 23, then end in Santiago on Oct 28 — what are the cheapest flights?"

Each stop is resolved to nearby airports automatically (e.g. "Patagonia" → BRC, USH, FTE, PUQ, BBA). Uses 1 API credit per leg (N-1 credits for N stops). Returns the cheapest flight per leg plus up to 3 alternatives so you can compare specific airport options (e.g. cheapest into Patagonia might be BRC, but you can see FTE/El Calafate options too).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoCountry code
hlNoLanguage code
tripYesOrdered list of stops. Each stop needs a location and a departure date. The last stop is the final destination (its date is unused).
stopsNoConnection stops filter: 0=Any, 1=Nonstop only, 2=1 stop or fewer, 3=2 stops or fewer
adultsNoNumber of adults
currencyNoCurrency code (e.g. GBP, EUR, USD)
max_priceNoMaximum price per leg
travel_classNo1=Economy, 2=Premium economy, 3=Business, 4=First
max_airports_per_stopNoMax airports to consider per stop when resolving location names (default 4)
Behavior5/5

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

With no annotations, the description discloses key behaviors: parallel leg search, automatic airport resolution (e.g., 'Patagonia' → BRC, USH, FTE, PUQ, BBA), per-leg API credit usage, and output format (cheapest per leg plus up to 3 alternatives).

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 compact yet dense: purpose, use case, example, credit cost, and output format all in a few sentences without redundancy.

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?

Given no annotations or output schema, the description covers the essential context: what the tool does, when to use it, how it behaves (parallel search, airport resolution, credits), and what it returns (cheapest per leg + alternatives). This 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?

Schema covers 100% of parameters with descriptions, so baseline is 3; the description adds semantic context for the trip parameter (parallel leg search, last stop date unused) and location resolution, justifying a 4.

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 opens with 'Plan a multi-leg trip by searching each leg in parallel,' a specific verb+resource, and positions it as 'Ideal for internal/domestic routing within a multi-country holiday,' distinguishing it from sibling tools like search_flights and plan_open_jaw_trip.

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 gives clear context ('Ideal for internal/domestic routing within a multi-country holiday') and a concrete example, implying when to use it instead of single-flight or open-jaw search tools, though it doesn't explicitly name exclusions.

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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