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Glama

Tuki — Travel Marketplace (Chile y Latinoamérica)

Detalle de un auto en arriendo

get_car_detail
Read-onlyIdempotent

Get full detail for a Tuki rental car: transmission, seats, bags, min driver age, price per day, city, canonical URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCar slug.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds value by disclosing the specific fields returned (transmission, seats, bags, etc.), giving the agent a clear picture of the response structure beyond what annotations provide.

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 a single, compact sentence that front-loads the core purpose and enumerates key fields. No wasted words, every element contributes to understanding the tool's functionality.

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 provides a comprehensive list of expected fields, making the tool predictable and complete for a read operation. The annotations cover safety, so no additional behavioral caveats are needed.

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

Parameters3/5

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

The single parameter 'slug' is described in the schema as 'Car slug', which fully covers its meaning. The description does not add any additional semantic information about the slug format or usage, so it stays at the baseline for full schema coverage.

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 clearly states the verb 'Get' and the resource 'full detail for a Tuki rental car', listing specific fields like transmission, seats, bags, min driver age, price per day, city, and canonical URL. This distinguishes it from sibling detail tools for other entity types.

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 implies this tool is for retrieving full details of a rental car when you have its slug, but it does not explicitly mention when to use it versus alternatives like search_car_rental or when not to use it. Sibling tools are similar in naming but for different entity types, so usage is implied rather than explicitly guided.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Every tool targets a distinct resource or action: get_* tools retrieve details for specific entity types, search_* tools query specific verticals, and list_* tools enumerate categories. The potential overlap between search_accommodations and search_hotels is explicitly disambiguated in descriptions, and search_unified vs per-vertical searches have clear routing rules.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: get_*_detail for lookups, search_* for queries, list_* for enumerations, and recommend as the sole one-word but still predictable exception. Naming is uniform with snake_case throughout, making the overall structure highly predictable.

Tool Count4/5

With 23 tools, the server is on the heavier side, but the breadth of verticals (accommodations, cars, events, experiences, hotels, destinations, bus routes, travel guides, solutions) justifies each tool's presence. The number is slightly above the ideal but still well-scoped for a multi-category marketplace.

Completeness5/5

The tool surface covers the full browsing and recommendation lifecycle: search and list across verticals, retrieve detailed information for any entity, access editorial travel guides, and generate checkout URLs for booking. No critical operations are missing for the server's purpose as a read-only recommendation and conversion layer.

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