Parcellaire — cadastre, DVF & DPE

Statistiques immobilières d'une commune

get_commune_stats

Read-onlyIdempotent

Retourne les statistiques d'une commune française : parcelles et bâtiments, prix au m² et volumes de transactions DVF par année, répartition des classes DPE, taux de propriétaires, logements vacants, etc. Identifier la commune par 'insee_id' (fiable) ou par 'commune' (nom ou code postal).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`commune`	No	Nom ou code postal de la commune, ex: 'Bordeaux'
`insee_id`	No	Code INSEE de la commune (prioritaire si fourni)

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 25, 2026
- addedInput schema / additionalProperties
```
Added value: +false
```

Changed6 schema fields changedSep 25, 2026

addedInput schema / properties / commune / anyOf

Added value: +[
+  {
+    "anyOf": [
+      {
+        "type": "string"
+      },
+      {
+        "const": "",
+        "type": "string"
+      }
+    ]
+  },
+  {
+    "type": "null"
+  }
+]

removedInput schema / properties / commune / type
```
Removed value: -"string"
```

addedInput schema / properties / insee_id / anyOf

Added value: +[
+  {
+    "anyOf": [
+      {
+        "maxLength": 5,
+        "minLength": 5,
+        "type": "string"
+      },
+      {
+        "const": "",
+        "type": "string"
+      }
+    ]
+  },
+  {
+    "type": "null"
+  }
+]

removedInput schema / properties / insee_id / maxLength
```
Removed value: -5
```
removedInput schema / properties / insee_id / minLength
```
Removed value: -5
```
removedInput schema / properties / insee_id / type
```
Removed value: -"string"
```

First observedSep 25, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds the behavioral nuance that insee_id is 'fiable' (reliable) and that commune can be name or postal code, which is useful context. It does not disclose any rate limits, error conditions, or output format, but given the annotations, this is acceptable.

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 two sentences with no filler. The core purpose is front-loaded, and the identification instructions are compact. Every sentence adds value.

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?

With no output schema, the description lists a wide range of returned statistics, which gives the agent a good idea of what to expect. Parameters are clearly explained. It does not mention edge cases like ambiguous commune names or empty results, but for a stats endpoint this is likely sufficient.

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 coverage is 100% with descriptions for both parameters. The description restates the parameter usage but adds a small value hint ('fiable' for insee_id) beyond the schema's 'prioritaire si fourni'. This is a minor addition, so baseline 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 states a specific verb ('Retourne') and resource ('statistiques d'une commune française'), listing concrete data types (parcelles, bâtiments, prix au m², volumes DVF, DPE, etc.). This clearly distinguishes it from sibling tools that handle individual properties, DPE queries, or searches.

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 clearly implies this is for commune-level aggregate statistics and explains how to identify the commune (by insee_id or name/postal code). However, it does not explicitly mention when not to use it or name alternative tools for specific sub-queries, so guidance is strong but not exhaustive.

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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