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French Property Valuation

real_estate_fr_valuation

Estimates a statistical property value range from nearby or municipal geolocated DVF comparable transactions. Use when: Estimate a French house or apartment from comparable recorded sales. Avoid when: Do not present the result as a certified appraisal or guaranteed sale price. Limitations: Valuation depends on the density of single-dwelling geolocated DVF comparables; VEFA/new and professional-use mutations are excluded, and built area may differ from Carrez area. DVF does not cover Alsace, Moselle or Mayotte; requests in those areas therefore return an empty result. Price: 0.030 USD per call via x402. Paid-call behavior: source records are not modified, but a successful invocation can consume the advertised x402 payment; the payment-required challenge is free, and repeating the tool after a completed paid invocation may require a new payment. Accepted x402 networks: eip155:8453, xrpl:0.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressNoOptional value for “address” as defined by this API contract. (minimum length 5; maximum length 250).
radius_mNoOptional value for “radius m” as defined by this API contract. (minimum 100; maximum 650; default 650).
code_inseeNoOptional value for “code insee” as defined by this API contract.
surface_m2YesRequired value for “surface m2” as defined by this API contract. (minimum 9; maximum 1000).
property_typeYesRequired value for “property type” as defined by this API contract. (allowed values: house, apartment).
lookback_yearsNoOptional value for “lookback years” as defined by this API contract. (minimum 1; maximum 5; default 3).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationYesStructured value returned for “location” as defined by this API contract.
radius_mYesStructured value returned for “radius m” as defined by this API contract.
confidenceYesConfidence indicator associated with an inferred or derived result. (allowed values: high, medium, low, insufficient).
surface_m2YesStructured value returned for “surface m2” as defined by this API contract.
comparablesYesStructured value returned for “comparables” as defined by this API contract.
limitationsNoKnown interpretation, source-coverage or freshness limitations for this result.
generated_atYesUTC timestamp at which this derived result was generated.
property_typeYesStructured value returned for “property type” as defined by this API contract.
source_statusYesAvailability status of the relevant upstream public source. (allowed values: ok).
lookback_yearsYesStructured value returned for “lookback years” as defined by this API contract.
estimated_valueYesStructured value returned for “estimated value” as defined by this API contract.
comparable_countYesStructured value returned for “comparable count” as defined by this API contract.
p25_price_per_m2YesStructured value returned for “p25 price per m2” as defined by this API contract.
p75_price_per_m2YesStructured value returned for “p75 price per m2” as defined by this API contract.
source_truncatedYesStructured value returned for “source truncated” as defined by this API contract.
source_total_countYesStructured value returned for “source total count” as defined by this API contract.
estimated_range_lowYesStructured value returned for “estimated range low” as defined by this API contract.
median_price_per_m2YesStructured value returned for “median price per m2” as defined by this API contract.
estimated_range_highYesStructured value returned for “estimated range high” as defined by this API contract.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / required
      Previous value: -[
-  "location",
-  "property_type",
-  "surface_m2",
-  "radius_m",
-  "lookback_years",
-  "source_status",
-  "source_total_count",
-  "source_truncated",
-  "comparable_count",
-  "median_price_per_m2",
-  "p25_price_per_m2",
-  "p75_price_per_m2",
-  "estimated_value",
-  "estimated_range_low",
-  "estimated_range_high",
-  "confidence",
-  "comparables",
-  "generated_at",
-  "limitations"
-]New value: +[
+  "location",
+  "property_type",
+  "surface_m2",
+  "radius_m",
+  "lookback_years",
+  "source_status",
+  "source_total_count",
+  "source_truncated",
+  "comparable_count",
+  "median_price_per_m2",
+  "p25_price_per_m2",
+  "p75_price_per_m2",
+  "estimated_value",
+  "estimated_range_low",
+  "estimated_range_high",
+  "confidence",
+  "comparables",
+  "generated_at"
+]
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no helpful annotations (all hints false), the description carries the full burden and delivers rich behavior: paid-call behavior, source records not modified, payment-required challenge free, potential repeat payment, DVF coverage gaps, and exclusion of VEFA/new/professional mutations. This goes far beyond what annotations provide and gives the agent a realistic model of side effects and limitations.

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 well-structured with labeled sections: purpose, use when, avoid when, limitations, price, paid-call behavior, and accepted networks. Every sentence carries useful information and the most important facts are front-loaded. There is no fluff 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?

This is a paid, complex API with an output schema, and the description covers purpose, usage boundaries, limitations, geographic exclusions, pricing, and payment side effects. The input schema separately documents required fields and the constraint that at least one of address or code_insee must be provided. Nothing critical is missing for an agent to invoke 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?

Schema description coverage is 100%, so the baseline is 3. The description adds loose semantic context by mentioning 'house or apartment' and 'built area may differ from Carrez area,' but it does not explain parameter selection rules such as the need for at least one of address or code_insee. The schema itself only repeats 'as defined by this API contract,' so the tool description adds minimal parameter-level meaning.

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?

The description states a specific verb and resource: 'Estimates a statistical property value range from nearby or municipal geolocated DVF comparable transactions.' The use-when line adds a concrete scenario. However, it does not explicitly distinguish itself from sibling tools like real_estate_fr_transactions or real_estate_fr_market, so it falls short of full sibling differentiation.

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?

The description provides explicit 'Use when' and 'Avoid when' guidance, including a clear caution against presenting results as certified appraisals. It also documents a major geographic limitation (Alsace, Moselle, Mayotte return empty results). It does not name alternative sibling tools for different use cases, so the guidance is clear but not fully comparative.

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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