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update_traveler_profile

Save specific travel preferences or experiences to your profile, ensuring future recommendations reflect your stated likes and dislikes.

Instructions

Save a learned travel preference or experience to the user's traveler profile.

Use when the user shares a durable preference, like, dislike, or trip experience that should
inform future recommendations — "Always takes a window seat", "Prefers boutique hotels over
chains", "Vegetarian". Don't save temporary logistics like "my flight lands at 3pm".

Saved entries come back from get_traveler_context in later sessions, which is how a preference
stated once is still known next time.

Requires a Gondola account (API key).

Args:
    profile_entry: The preference or experience to save. Be specific and actionable.
        Good: "Prefers ocean-view rooms". Bad: "Liked the hotel".

Returns:
    Confirmation of the saved entry, or an error message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profile_entryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate a non-destructive write (readOnlyHint=false, destructiveHint=false). The description adds useful behavioral context: requires API key, returns confirmation/error, and entries persist across sessions.

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?

Well-structured with clear purpose, usage guidelines, parameter/return details. Every sentence adds value, though could be slightly more concise.

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?

Covers prerequisites, parameter semantics, return values, and persistence. With only one parameter and output schema, it is quite complete. Could mention if updating existing entries replaces or appends, but not critical.

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 0%, so the description carries full burden. It explains the parameter profile_entry with specificity and actionability guidance, including good/bad examples.

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 uses a specific verb ('Save') and resource ('traveler profile'), clearly distinguishing this write operation from siblings like get_traveler_context. It explicitly states what is saved: durable preferences, likes, dislikes, trip experiences.

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 guidance: use for durable preferences (examples given), not for temporary logistics. Also notes the prerequisite of a Gondola account and explains that saved entries persist and come back via get_traveler_context.

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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