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Glama

get_traveler_context

Read-only

Retrieve your saved travel context, including loyalty programs and preferred airlines and hotels, to personalize flight, hotel, and car recommendations for each trip.

Instructions

Get the user's saved travel context to personalize recommendations.

Returns the user's loyalty programs and elite tiers, home airport, preferred airlines and
cabin, preferred hotel chains, typical trip patterns (business vs leisure, budgets, frequent
destinations), and 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 across
hotel, flight, and car recommendations — 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.

Requires a Gondola account (API key).

Returns:
    Formatted travel context, or instructions to build one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the read-only safety profile is covered. The description adds genuinely useful behavioral context beyond the annotations: the contents of the returned context, that preferences may be learned from past conversations, that a Gondola account/API key is required, and the fallback behavior of returning 'instructions to build one.' No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary purpose, then covers contents, usage timing, alternative routing, auth, and return format in a logical sequence. It is slightly redundant in listing the contents and then adding a 'Returns:' line, but every sentence still contributes meaningful guidance.

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

Completeness4/5

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, the description is quite complete: it covers what data is included, when to call it, how to use it, which sibling to use for raw evidence, auth requirements, and the fallback response. It does not mention the sibling get_travel_profiles, but the description's emphasis on being 'the single best source' gives enough signal for an agent to select this tool.

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 zero parameters, so the schema provides nothing to describe; the baseline for 0 params is 4. The description does not need to explain parameter meaning, and it appropriately focuses on what the tool returns instead of parameter details.

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 a specific verb and resource ('Get the user's saved travel context') and states its purpose ('to personalize recommendations'). It explicitly differentiates itself from the close sibling get_past_trips: 'For raw evidence from actual past reservations... use get_past_trips.' An agent can clearly tell what this tool does and what it is not.

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?

Provides explicit invocation guidance: 'Call this once at the start of a travel or planning session' and tells the agent how to use the output, 'weigh it across hotel, flight, and car recommendations.' It also names the alternative for a different need, get_past_trips, and adds the auth prerequisite of a Gondola account.

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