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Glama

Gondola Award Travel Search

get_traveler_context

Read-only

Get the user's saved travel context: loyalty programs and elite tiers, home airport, preferred airlines and cabin, preferred hotel chains, typical trip patterns (business vs leisure, budgets, frequent destinations), plus any preferences they've stated or that have been learned from past conversations. Call this once at the start of a travel or planning session and weigh it when recommending hotels, flights, or cars — it is the single best source of who this traveler is. For raw evidence from actual past reservations, routes, hotels, airlines, or flight seats, use get_past_trips.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already mark readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context: it aggregates stated and learned preferences and frames itself as 'the single best source of who this traveler is.' It does not contradict the annotations.

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 three sentences with no filler: definition, usage instruction, and alternative tool routing. It is front-loaded with the core purpose and every sentence earns its place.

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?

For a zero-parameter read-only tool with an output schema and annotations, the description fully covers what data the tool returns, when to call it, how to use its output, and how it relates to a key sibling tool. Nothing essential 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?

The tool has 0 parameters, so schema description coverage is effectively complete. No parameter explanation is needed, and the description does not introduce any misleading parameter-related information.

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 what the tool does: 'Get the user's saved travel context' and enumerates the contents (loyalty programs, home airport, preferred airlines, hotel chains, trip patterns). It also distinguishes itself from get_past_trips by noting the latter provides raw past reservation evidence, so an agent can tell them apart.

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 gives explicit usage direction: call it once at the start of a travel or planning session and weigh it when recommending hotels, flights, or cars. It also names a specific alternative (get_past_trips) for raw past-reservation evidence, providing clear when-not-to-use 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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct resource and action; no two tools have overlapping purposes. For example, search_hotels, get_hotel_details, get_hotel_reviews, and get_hotel_stats all address different aspects of hotel research.

Naming Consistency5/5

Tool names follow consistent patterns: search_ for searches, get_ for retrievals, book_ for bookings, and a few standalone verbs like cancel_, create_, delete_. All use snake_case with no mixing of conventions.

Tool Count4/5

With 31 tools, the server is on the high side but covers a broad domain (hotels, flights, vehicles, loyalty, payments). Most tools are justified, though a few hotel analysis tools could potentially be consolidated.

Completeness3/5

Hotels and vehicles have near-complete lifecycle coverage (search, details, book, manage), but flights are missing a book_flight tool, and hotel cancellation is not present. These gaps limit completeness.