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Landhaus Apartments Prägant

get_rates

Read-only

Get current rates for apartments at Landhaus Prägant, Bad Kleinkirchheim, Austria.

Prices are PER APARTMENT PER NIGHT, not per person. Additional: cleaning fee (one-time) + tourist tax (per person/night). Data is live from the property management system.

This is the data-only version — for a visual rates card, call render_rates_card() with the same arguments after reviewing this result.

Args: month: e.g. '2026-07' or 'july' or 'juli'. Leave empty for next month. guests: Number of guests (1-5, default: 2). language: "de" (default) or "en" — match the conversation language.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthNo
guestsNo
languageNode

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already declare the tool read-only and non-destructive. The description adds meaningful behavioral context: pricing is per apartment per night rather than per person, fees are itemized, and data is live from the PMS. This goes beyond the annotations and clarifies how to interpret the returned rates.

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 and front-loaded with the core purpose, followed by critical pricing semantics, the sibling alternative, and then a clearly delineated Args section. Each sentence contributes unique information with no filler or repetition.

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?

Despite having no output schema, the description provides enough context for an agent to call the tool correctly: what data it returns, how to interpret cost semantics, which arguments to pass, and what to do next. Nothing essential is missing.

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

Parameters5/5

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 responsibility for explaining parameters. It does so thoroughly: month shows example formats and empty default, guests explains range and default, and language lists allowed values with a matching heuristic. This fully compensates for the schema's lack of descriptions.

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 begins with a concrete verb and resource: 'Get current rates for apartments' at a specific property and location. It also explicitly contrasts itself with render_rates_card as the 'data-only version,' clearly differentiating it from a key sibling tool.

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?

It provides explicit usage direction: use this for data-only rates, then call render_rates_card() with the same arguments if a visual card is needed. It also gives per-argument usage hints such as month formats, default behavior, guest count limits, and language matching to the conversation.

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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