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Gondola Award Travel Search

by ai.gondola
OverviewDiscussionsAdmin

update_traveler_profile

Save a learned travel preference or experience to the user's traveler profile. Use when the user shares preferences, likes, dislikes, or trip experiences that should inform future recommendations. Examples: 'Prefers boutique hotels over chains', 'Always takes a window seat', 'Vegetarian — recommend plant-based restaurants', 'Hated ground floor rooms'. Don't save temporary logistics like 'my flight lands at 3pm'. Entries are appended, so saving one preference never overwrites another.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profile_entryYesThe preference or experience to save. Be specific and actionable. Good: 'Prefers ocean-view rooms'. Bad: 'Liked the hotel'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "title": "Result",
+      "type": "string"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "update_traveler_profileOutput",
+  "type": "object"
+}
  2. Changed4 schema fields changed
    • addedInput schema / properties / profile_entry / description
      Added value: +"The preference or experience to save. Be specific and actionable. Good: 'Prefers ocean-view rooms'. Bad: 'Liked the hotel'."
    • removedInput schema / properties / profile_entry / title
      Removed value: -"Profile Entry"
    • removedInput schema / title
      Removed value: -"update_traveler_profileArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "title": "Result",
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "update_traveler_profileOutput",
-  "type": "object"
-}New value: +null
  3. Added

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that 'Entries are appended, so saving one preference never overwrites another,' which is important persistence behavior. It also provides real examples of acceptable and unacceptable entries, clarifying the expected effect of the operation.

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 compact, front-loaded with the core purpose, and every sentence adds value: purpose, usage trigger, examples, exclusions, and append behavior. No filler or redundant detail.

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 single-parameter, append-only tool with schema coverage and annotations provided, the description fully covers what the agent needs: what to save, how to phrase it, what not to save, and the non-destructive nature of the operation. Nothing required for correct invocation 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 input schema already documents the single parameter thoroughly, including good and bad examples. The tool description adds further guidance about specificity and actionable entries, which reinforces but does not fully duplicate the schema content.

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 states a specific verb ('save') and resource ('learned travel preference or experience to the user's traveler profile'), making the tool's function clear. It also distinguishes itself from nearby read-oriented siblings like get_traveler_context by focusing on persisting preferences rather than retrieving them.

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 explicitly says 'Use when the user shares preferences, likes, dislikes, or trip experiences that should inform future recommendations' and gives concrete counterexamples. It also warns against saving temporary logistics like flight arrival times, giving the agent clear guardrails for when not to invoke the tool.

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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