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Glama

Rechercher des mutations DVF à une adresse

query_dvf_property_transactions

Search official French DVF property sales by year, department, and address; filter by price and group mutation records to avoid counting one sale twice.

Instructions

Interroge le fichier départemental officiel DVF, filtre une adresse et un prix éventuel, puis regroupe les lignes par id_mutation afin de ne pas compter plusieurs fois une même vente. DVF ne publie pas l’identité des parties.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
date_toNo
date_fromNo
departmentYes
postal_codeNo
street_nameYes
target_valueNo
max_mutationsNo
street_numberYes
value_toleranceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral burden and it does disclose two meaningful traits: rows are grouped by id_mutation to avoid double-counting a single sale, and DVF does not publish the identity of the parties (a data-limitation notice). However it omits read-only confirmation, whether max_mutations truncates results, rate limits, and return shape for a 10-parameter query tool.

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 sentences, front-loaded with the core verb and resource, followed by the deduplication and privacy caveats. No filler. Slightly compressed given the amount of unexplained surface area, but structurally sound.

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

Completeness2/5

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

For a 10-parameter tool with no annotations and no output schema, the description is too thin: it does not explain most parameters, the return format, or how results are capped. An agent can identify the tool's gist but lacks enough to invoke it confidently.

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

Parameters2/5

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

Schema description coverage is 0% and there are 10 parameters, so the description must compensate, but it only hints at address filtering and an optional price filter ('un prix éventuel'). It says nothing about year, department, date_from/date_to, max_mutations, or value_tolerance, leaving most inputs unexplained.

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?

States a specific verb chain (interroge, filtre, regroupe) on a clearly named resource (fichier départemental officiel DVF) and even describes the deduplication intent. It is unambiguous what the tool does. It doesn't explicitly contrast with siblings, but no sibling overlaps this real-estate domain, so differentiation is moot.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use or when-not-to-use guidance, nor any named alternative. Usage must be inferred from the description of filtering address/price. Nothing tells the agent under what circumstances this tool is the right choice.

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