HelpMyAgent

French Real-estate Market

real_estate_fr_market

Summarizes local French property transaction prices and yearly trends from geolocated DVF data. Use when: Summarize a French local property market from recorded transactions. Avoid when: Do not use as a listing-price index or a certified appraisal. Limitations: Statistics use up to 200 geolocated DVF single-dwelling mutations per year and residential property type; VEFA/new and professional-use mutations are excluded, with truncation exposed explicitly. DVF does not cover Alsace, Moselle or Mayotte; requests in those areas therefore return an empty result. Price: 0.020 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

Name	Required	Description	Default
`address`	No	Optional value for “address” as defined by this API contract. (minimum length 5; maximum length 250).
`radius_m`	No	Optional value for “radius m” as defined by this API contract. (minimum 100; maximum 650; default 650).
`code_insee`	No	Optional value for “code insee” as defined by this API contract.
`property_type`	No	Optional value for “property type” as defined by this API contract. (default all; allowed values: all, house, apartment).	all
`lookback_years`	No	Optional value for “lookback years” as defined by this API contract. (minimum 1; maximum 5; default 5).

Output Schema

TableJSON Schema

Name	Required	Description
`yearly`	Yes	Structured value returned for “yearly” as defined by this API contract.
`summary`	Yes	Compact derived summary of the returned records.
`location`	Yes	Structured value returned for “location” as defined by this API contract.
`radius_m`	Yes	Structured value returned for “radius m” as defined by this API contract.
`limitations`	No	Known interpretation, source-coverage or freshness limitations for this result.
`generated_at`	Yes	UTC timestamp at which this derived result was generated.
`property_type`	Yes	Structured value returned for “property type” as defined by this API contract.
`sampled_count`	Yes	Structured value returned for “sampled count” as defined by this API contract.
`source_status`	Yes	Availability status of the relevant upstream public source. (allowed values: ok).
`coverage_scope`	Yes	Structured value returned for “coverage scope” as defined by this API contract. (allowed values: radius, commune).
`lookback_years`	Yes	Structured value returned for “lookback years” as defined by this API contract.
`sample_truncated`	Yes	Structured value returned for “sample truncated” as defined by this API contract.
`source_total_count`	Yes	Structured value returned for “source total count” as defined by this API contract.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 16, 2026

changedOutput schema / required

Previous value: -[
-  "location",
-  "coverage_scope",
-  "radius_m",
-  "property_type",
-  "lookback_years",
-  "source_status",
-  "source_total_count",
-  "sampled_count",
-  "sample_truncated",
-  "summary",
-  "yearly",
-  "generated_at",
-  "limitations"
-]New value: +[
+  "location",
+  "coverage_scope",
+  "radius_m",
+  "property_type",
+  "lookback_years",
+  "source_status",
+  "source_total_count",
+  "sampled_count",
+  "sample_truncated",
+  "summary",
+  "yearly",
+  "generated_at"
+]

AddedSep 10, 2026

TDQS

A4.3/5.0

Behavior5/5

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

The description discloses that the tool is a paid call with a price and that it does not modify source records, while noting that successful invocations consume payment. It also details limitations such as geographic exclusions and truncation. Since annotations are all false and provide no hints, the description carries the full burden and does so thoroughly.

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?

The description is structured into clear sections (Use when, Avoid when, Limitations, Price, Paid-call behavior, Networks) and front-loads the primary purpose. While it is somewhat long, each section provides distinct, necessary information without redundancy.

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?

The description covers essential operational aspects: usage context, exclusions, limitations, cost, payment behavior, and geographic coverage. It does not mention the required at-least-one-of-address/code_insee constraint, but that is present in the schema description, so the description is complete enough given the presence of an output schema.

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 schema covers all parameters with descriptions and constraints, but the parameter descriptions are generic ('as defined by this API contract') and provide no additional meaning. The tool description does not elaborate on parameter usage, so it adds no value beyond the schema. With 100% coverage, a baseline of 3 is appropriate.

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 clearly states the tool's function: summarizing French property transaction prices and yearly trends from DVF data. It uses a specific verb ('summarizes') and resource ('French property transaction prices and yearly trends'), distinguishing it from sibling real_estate tools like real_estate_fr_transactions (raw transactions) and real_estate_fr_valuation (appraisal).

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 includes explicit 'Use when' and 'Avoid when' sections, clarifying appropriate scenarios and explicitly excluding use as a listing-price index or certified appraisal. It does not name specific sibling tools but provides sufficient guidance for an agent to select this tool over alternatives.

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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