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Rents

rents
Read-onlyIdempotent

Get INE housing rent index (IPVA) changes over the last 1 and 5 years and since 2015 for Spanish municipalities, districts, provinces and regions, with province, region and Spain benchmarks.

Instructions

How housing rents have changed in a place: INE's rent index (IPVA, 2015 = 100) with the change over the last year, five years and since 2015, against province, region and Spain.

Covers municipalities over 10,000 residents, districts of provincial capitals, provinces and
regions (not the Basque Country or Navarra). Gives changes, not rents in euros.

Input Schema

NameRequiredDescriptionDefault
placeYesPlace name or INE code: municipality ('Valladolid' or '47186'), province ('41'; a bare name like 'Sevilla' means the city), autonomous community ('Cataluña' or 'CA09'), district ('4718603') or census tract ('4718603012'). 'Name, Province' picks between same-named towns.

Output Schema

NameRequiredDescriptionDefault
dataYes
checksNo
sourcesYes
confidenceYesLowest confidence across inputs: high, medium or low. Never state a conclusion more strongly than this.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare this a read-only, idempotent, open-world read, so the safety profile is covered. The description adds behavioral substance beyond that: geographic coverage limits, the exclusion of two regions, and the crucial unit caveat that outputs are index changes rather than euro rents. It doesn't state update frequency or the reference period granularity.

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?

Two tight paragraphs, front-loaded with the core purpose before coverage caveats. Coverage of provinces and regions is mentioned in both paragraphs, a minor redundancy, but nothing is wasted overall.

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?

An output schema exists, so return values need not be documented — and the description still adds the key interpretive context that values are changes, not euro amounts. Combined with the full parameter documentation and geographic scope, an agent has everything needed to call it correctly.

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

Parameters3/5

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

The single `place` parameter has 100% schema description coverage, including the accepted code formats and disambiguation syntax, so the schema does the heavy lifting. The description adds nothing about parameter syntax or format beyond what the schema already says.

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 and resource — how housing rents have changed — and names the exact data source (INE's IPVA, 2015 = 100) plus the measures returned (1/5-year and since-2015 change). The line 'Gives changes, not rents in euros' sharply differentiates it from sibling tools like income or price_band that might otherwise be confused with rent costs.

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?

Coverage is spelled out precisely (municipalities over 10,000 residents, districts of provincial capitals, provinces, regions) and exclusions are stated (not the Basque Country or Navarra), which functions as implicit when-not guidance. It stops short of naming an alternative tool to use for excluded areas or for different geographies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.