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Rent-control reference rents

rent_control

Check legal rent ceilings for a French address in Paris or Lyon. Get reference, maximum, and minimum rent per m²/month by rooms, construction period, and furnishing, with explicit notice if not covered.

Instructions

Loyer de référence, loyer de référence majoré (the legal ceiling) and minoré, in €/m²/month, for a rent-controlled area — by number of rooms, construction period and furnished status. Covers only the areas whose authority publishes an open grid (Paris, Métropole de Lyon); the response states explicitly when an address is not covered instead of guessing. Sources: Ville de Paris, Métropole de Lyon.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
roomsNoNumber of rooms (pièces)
periodNoConstruction period label, e.g. '1946-1970'
addressYesAddress in France
furnishedNoFurnished (true) or unfurnished (false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It reveals the output unit, the coverage limitation, and the explicit no-guessing behavior when an address is not covered. It also names data sources, adding trustworthiness. Minor omissions like default behavior when optional parameters are absent are not addressed.

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?

Three compact sentences deliver the core output, scope, non-guessing behavior, and sources with no redundancy. The most important information is front-loaded, and every sentence earns its place.

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

Completeness4/5

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

Given there is no output schema, the description adequately explains return values and edge-case behavior. It covers scope, units, and non-covered addresses. A small gap is that the optional parameters' behavior when omitted is not specified, but this does not seriously impair correct invocation.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds context by linking rooms, construction period, and furnished status to the output, and clarifies that address must fall within covered areas. It does not add syntax or format details beyond what the schema already provides.

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 identifies the exact deliverable: loyer de référence, majoré (legal ceiling), and minoré in €/m²/month for rent-controlled areas, segmented by rooms, construction period, and furnished status. This clearly distinguishes it from siblings like rent_estimate by specifying legal reference rents rather than market estimates.

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?

It gives clear usage context: the tool applies to rent-controlled areas with a published open grid, notably Paris and Métropole de Lyon, and explicitly handles non-covered addresses. It does not name alternative tools or state exclusions explicitly, but the scope is concrete enough for an agent to decide when to invoke it.

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