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cturkieh

France Data MCP

inspect_site

Read-onlyIdempotent

Inspect a healthcare site by aggregating FINESS identification, administrative status, attached professionals, and historical timelines in a single call.

Instructions

Vue 360 d'un établissement de santé en 1 appel (V0.10). Pendant naturel de panorama_sante_territoire côté site : agrège en parallèle (a) identification FINESS DREES (raison sociale, adresse, téléphone), (b) statut administratif SIRENE via le resolver SIRET (verdicts site + groupe, best_match, SIREN explorés, dinum_errors, explication LLM-friendly), (c) professionnels rattachés via num_finess (sample borné + flag truncated si le site a plus de PS — PAS un count total), (d) historique INSEE (timeline périodes administratives par SIRET candidat).

Remplace 3 appels MCP individuels (verifier_site_actif + rpps_dans_etablissement + historique_etablissement) par 1 seul. Utile pour : prospection (qualifier un site avant outreach), audit territorial (cross-check rapide d'un FINESS suspect), enrichissement CRM en batch.

Format de retour : objet LookupResult. Quand found: true, payload avec 4 sections (finess, statut_site, professionnels, historique). La section historique peut être available: false quand le FINESS existe mais qu'aucun SIRET candidat n'a été identifié (RPPS vide + DINUM 0 match) — dans ce cas le message reprend celui de historique_etablissement. Quand num_finess est absent de FINESS DREES, retourne {found: false, lookupStatus: 'not_found', message}.

Coût : 3 sous-appels parallèles. Cache PostgreSQL absorbe la duplication FINESS-RPC ; le pivot RPPS→DINUM est exécuté en double (verifier + historique partagent la cascade), surcoût p95 ≤ 600 ms — acceptable pour un agrégateur. Pour les besoins ciblés (juste le verdict, juste l'historique), préférer les tools individuels. Payload lourd (~7K tokens) : passer historique_detail: false pour un retour allégé (résumé au lieu des timelines SIRENE complètes) en usage batch.

Alias acceptés : numFiness/finess/idnum_finess.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_finessYesNuméro FINESS exact 9 chiffres. Ex: '590048997'.
rpps_limitNoNombre max de PS dans `professionnels.sample`. `professionnels.count` = taille du sample (≤ cette borne), pas le total du site ; `truncated: true` signale qu'il y a davantage de PS. Borné [1, 50]. Défaut 10.
historique_detailNoInclure les timelines SIRENE détaillées dans `historique.siret_timelines` (défaut true). `false` = payload allégé (~7K tokens en moins) : `historique` ne porte qu'un `resume` (counts) + un pointeur vers `historique_etablissement`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYes
lookupStatusYes
keyNoClé recherchée (SIREN, num_finess, code INSEE, …).
messageNoExplication actionnable quand `found=false` (cause probable + remédiation).
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds substantial behavioral context: parallel sub-calls, caching, cost (≤600ms p95), heavy payload (~7K tokens), and edge cases (historique available false, not found return format). No contradiction with annotations.

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 detailed but well-structured, front-loading the purpose and then breaking into clear sections with bullet points. Every sentence provides value, though it is slightly verbose. It earns a 4 for being informative without being overly terse.

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 the tool's complexity as an aggregator, the description covers return format, edge cases, performance considerations, and alternatives. With 100% schema coverage and an output schema present, the description is considered complete for effective use.

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?

Schema description coverage is 100%, baseline is 3. The description adds meaning beyond schema by explaining the effect of historique_detail (payload reduction) and rpps_limit behavior (sample bound vs total count with truncated flag). This extra context justifies a 4.

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 it provides a 360-degree view of a healthcare establishment in a single call, aggregating multiple data sources. It explicitly names the verb 'agrège' (aggregates) and identifies the resource as a site by FINESS. It distinguishes from sibling tools by naming the three tools it replaces (verifier_site_actif, rpps_dans_etablissement, historique_etablissement).

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?

The description explicitly states when to use: for prospection, audit territorial, and CRM enrichment. It also provides when-not-to-use guidance by recommending individual tools for targeted needs (just verdict or just history). It suggests using historique_detail: false for lightweight batch usage, offering clear context.

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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