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hotel_info

Get canonical facts about Yasha Hotel: name, 3-star rating, address (27 Rue Joseph Junck, L-1839 Luxembourg, 100 m from Luxembourg central station), phone, email, amenity list, direct-booking discount percentage vs OTAs, and breakfast price per guest per night. Use this to answer any traveler question about the property. Prices are in euro cents.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full disclosure burden, and it does useful work: it establishes this is a static read of authoritative 'canonical facts' and explicitly states the unit convention ('Prices are in euro cents'), which prevents a costly interpretation error. It stops short of stating that the data is cached/static or noting any rate or freshness characteristics.

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 verb and resource, then a dense field enumeration, then usage and unit notes. The field list is long but justified because the input schema is empty, so the payload has to be described somewhere; the final unit sentence is short and high-value.

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?

With no output schema and an empty input schema, the description must define both the call semantics (zero-arg fetch) and the return content, and it does both exhaustively, including field-by-field contents and currency units. Nothing an agent needs in order to call this tool or interpret its result 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 takes zero parameters, so per the rubric this is a baseline 4. The description correctly adds no parameter claims and instead spends its space on the payload, which is the right allocation.

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?

States a specific verb ('Get') plus the exact resource ('canonical facts about Yasha Hotel') and enumerates the returned fields: name, rating, address, phone, email, amenities, discount, breakfast price. It is easily distinguished from data-returning siblings like list_rooms or check_availability, which cover rooms or availability rather than the property record.

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

Usage Guidelines3/5

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

'Use this to answer any traveler question about the property' gives a use context but is over-broad and does not carve out boundaries against siblings such as list_rooms or list_extras, which also serve property-related questions. Usage is implied rather than routed.

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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