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Check airline cabin fit

check_airline_fit
Read-onlyIdempotent

Check whether a bag fits an airline's cabin-bag and/or personal-item (under-seat) limits. Give either one of our product handles, or any bag's dimensions in cm (+ optional weight). Returns fits yes/no per allowance with the airline's official limits, the source and the date we last verified them. Orientation-independent; strict (no tolerance), like gate sizers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoStore market: 'ee' = kohvrimaailm.ee (Estonian), 'lv' = koferuveikals.lv (Latvian). Defaults to the domain this server was reached on. Prices, titles and links follow the market.
airlineYesAirline name, slug or IATA code, e.g. 'Ryanair', 'airbaltic', 'W6'.
bag_typeNoLimit the check to one allowance type. Omit to check all.
weight_kgNoBag weight in kg (used with dimensions_cm).
dimensions_cmNoOuter bag dimensions in cm including wheels and handles.
product_handleNoOur product handle or URL. Alternative to dimensions_cm.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish readOnly, idempotent, non-destructive, non-open-world. The description adds genuinely non-obvious behavior: the check is orientation-independent, strict with no tolerance ('like gate sizers'), and returns freshness metadata (source + last-verified date). The gate-sizer analogy is a real behavioral disclosure beyond structured fields.

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?

Three tight sentences: purpose first, then input modes, then return shape. Every clause carries information (allowance types, input alternatives, strictness, verification metadata) with no filler.

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?

With no output schema, the description carries the return-value burden and does so explicitly: yes/no per allowance plus official limits, source, and verification date. Combined with the annotations covering the safety profile and the schema covering all six parameters, nothing needed to call this correctly is missing.

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 description coverage is 100%, so the baseline is 3. The description earns above baseline by clarifying that dimension comparison is orientation-independent and that weight is optional and only meaningful alongside dimensions_cm, adding interpretation the schema's per-field text does not.

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?

States a specific verb and resource ('Check whether a bag fits an airline's cabin-bag and/or personal-item limits') and scopes it precisely to cabin/under-seat allowances, which no sibling (get_product, list_airlines, recommend_for_trip, search_products, store_policies) covers. An agent can identify this as the fit-checking tool without opening the schema.

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

Usage Guidelines3/5

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

The description tells the agent HOW to supply the bag ('either one of our product handles, or any bag's dimensions in cm (+ optional weight)'), which is useful input guidance, but never says when to prefer this tool over siblings like recommend_for_trip or get_product, nor when-not to use it. Usage is implied rather than framed against alternatives.

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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