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france-data-mcp

by io.github.cturkieh

compare_adresse_cnam_vs_finess

Read-onlyIdempotent

Compare l'adresse d'un centre de santé côté CNAM (Annuaire santé Ameli) vs FINESS DREES pour un même num_finess. Primitive brute SANS interprétation métier — retourne les deux adresses, un score_dice (0..1, informatif ; null si non comparable car finess_absent) et un statut. Le caller décide quoi faire de la divergence.

Utilité : signaler un déménagement propagé par une source mais pas (encore) par l'autre (ex: CNAM '5 RUE DE L'ARQUEBUSE AUTUN' vs FINESS '15 BD BERNARD GIBERSTEIN AUTUN' pour le même FINESS). Équivalent côté centre de santé de compare_raison_sociale_finess_vs_rpps.

Statut (présent uniquement sur found: true) :

  • match : adresses strictement égales après normalisation

  • match_after_abbreviation_normalization : égales après expansion des abréviations de voie FR (R/RUE, BD/BOULEVARD, AV/AVENUE…) — MÊME adresse, simple abréviation DREES vs CNAM, PAS un déménagement

  • divergent_after_normalization : adresses réellement différentes (déménagement non synchronisé entre sources)

  • finess_absent : le CDS existe côté CNAM mais le num_finess est absent de FINESS DREES (latence sync bimensuelle)

Format : objet LookupResult discriminé par found. Si le num_finess n'est PAS un centre de santé CNAM, le tool retourne {found: false, lookupStatus: 'not_found', message} (utiliser etablissement_by_finess pour un établissement non-CDS).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_finessYesNuméro FINESS exact (9 chiffres).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoClé recherchée (SIREN, num_finess, code INSEE, …).
foundYes
messageNoExplication actionnable quand `found=false` (cause probable + remédiation).
lookupStatusYes

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is known safe. Description adds detailed behavior: returns two addresses, score_dice (with null case), statut with four cases explaining divergence, and handles not_found for non-CDS. No contradictions.

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?

Description is long but well-structured with bullet points for statut cases and clear examples. Could be slightly more concise, but the detail is justified given the tool's complexity.

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?

Given output schema exists and the tool has multiple status cases, description fully explains each statut, score_dice behavior, and the not_found scenario with alternative guidance. Very complete.

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

Parameters4/5

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

Only one parameter num_finess, with schema description covering format. Description adds semantics that the finess must correspond to a CDS, which is not in the schema, enriching understanding.

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?

Description clearly states it compares addresses from CNAM vs FINESS for a given num_finess, and distinguishes itself by noting it is the 'equivalent côté centre de santé de compare_raison_sociale_finess_vs_rpps'.

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

Usage Guidelines5/5

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

Explicitly says when to use (signal a move propagated by one source but not the other), provides an example, and states when not to use (non-CDS finess) with an alternative tool (etablissement_by_finess).

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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TDQS

A4/5.0
Disambiguation3/5

While tools have distinct purposes, there is overlap among several similar tools (e.g., multiple professional and establishment search tools). The detailed descriptions help differentiate, but an agent may struggle to choose correctly among them.

Naming Consistency2/5

Naming mixes French and English, with no consistent pattern (e.g., 'enrichir_concurrents' vs 'inspect_site', 'etablissement_by_finess' vs 'etablissements_finess_in_radius'). This inconsistency makes the toolset harder to navigate.

Tool Count3/5

36 tools is high but justified given the broad domain. However, there are multiple tools for similar tasks (e.g., four professional search tools), suggesting some redundancy. The scope is borderline but acceptable.

Completeness4/5

The toolset covers a wide range of needs for French health data analysis: establishments, professionals, population, geocoding, demographics, and composite analyses. Few obvious gaps exist, though some specialized tasks might require additional integration.

Resources