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ANIME INTELLIGENCE / AI PURCHASE INTELLIGENCE

Travel Shopping Intelligence

travel_shopping_intelligence
Read-only

Search and rank travel inventory for AI agents. Use for hotels/accommodations now; car rentals are supported when Booking.com Demand credentials are configured. Attractions and transfers use provider beta endpoints. Returns a recommended option, alternatives, price signals and a booking route when the provider supplies one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
rowsNo
roomsNo
adultsNo
originNoIATA airport code for flight search.
airportNo
checkinNo
countryNo
checkoutNo
childrenNo
currencyNoJPY
verticalNoaccommodation
cabin_classNoeconomy
destinationNoIATA airport code for flight search.
return_dateNoOptional YYYY-MM-DD return date.
search_queryNo
booker_countryNojp
departure_dateNoYYYY-MM-DD for flight search.
max_connectionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/non-destructive, so the bar is lower. The description adds genuinely new behavioral facts the annotations cannot convey: per-vertical availability, a credential prerequisite, and beta endpoint status. It does not describe latency, rate limits, or failure behavior.

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?

Front-loaded with the core verb and resource, then qualifications. Four dense sentences with little waste, though the closing sentence about return contents overlaps the output schema.

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

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 19-parameter tool with zero required parameters, an agent needs to know which parameter combinations are valid per vertical (e.g. city/dates for accommodation vs. origin/destination/departure_date for flight); the description never says this. Output schema and annotations cover returns and safety, but the parameter-combination gap is substantial.

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

Parameters2/5

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

Schema description coverage is only 21% across 19 parameters, so the schema does not carry the load. Aside from implying the 'vertical' values (accommodation/flight/car/attraction/transfer), the description explains nothing about city being an integer ID, IATA codes, date formats, currency default, or which params any given vertical needs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Search and rank travel inventory') and scopes it to AI agents, which separates it from the product-oriented 'shopping_intelligence' siblings. It doesn't explicitly name a sibling to contrast against, but the travel domain and vertical list make its remit clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives real usage context: accommodations work now, cars need Booking.com Demand credentials, attractions/transfers are beta. That tells an agent which verticals are viable. It stops short of naming alternatives or stating when NOT to use this 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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