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cturkieh

France Data MCP

rpps_dans_etablissement

Read-onlyIdempotent

Lists health professionals (RPPS) working at a FINESS establishment, with breakdown by practice mode (liberal vs salaried) and optional public agent or student categories. Ideal for verifying who works in a hospital, lab, or clinic.

Instructions

Liste les PS rattachés à un établissement FINESS (num_finess 9 chiffres). Pivot RPPS↔FINESS — répond à "qui travaille dans ce labo / hôpital / clinique ?". Le mode_exercice distingue les libéraux exerçant sur place (vacations) des salariés. Couverture : RPPS expose ce lien quand le PS l'a déclaré ; salariés CH/CHU/cliniques bien couverts.

Sortie compacte : coords et distance_km sont null (le tool est par établissement, pas spatial — pour la géoloc, pivoter via etablissement_by_finess sur le num_finess). Catégorie par défaut : Civil (C, ~97 % — libéraux, salariés privés, hospitaliers contractuels). Opt-in : include_agents_publics: true ajoute Agents publics (M, ~0,3 % — PH titulaires, ARS, CNAM, Éducation nationale, PMI, militaires SSA) ; include_etudiants: true ajoute Étudiants (E, ~2,5 % — internes, externes, élèves IDE/SF). Réf : https://mos.esante.gouv.fr/NOS/TRE_R09-CategorieProfessionnelle/. Source : Annuaire Santé, Agence du Numérique en Santé (ANS) — Licence Ouverte v2.0

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_finessYes
include_etudiantsNo
include_agents_publicsNo
limitNo
include_freshnessNoSi true, ajoute un champ `data_freshness` au payload (dans `query_metadata` si présent, sinon à la racine) listant la dernière ingestion réussie par source (FINESS, Ameli, RPPS, CDS) avec `staleness_days`. Opt-in pour ne pas alourdir les payloads par défaut. Cache 5min côté serveur — coût négligeable.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNombre d'entrées retournées dans `results` (post-troncature).
totalNoEffectif réel avant troncature. Présent sur les tools de nomenclature paginés (lister_*) : `count` = échantillon, `total` = total réel, re-appeler avec un `limit` supérieur si `truncated`.
truncatedNotrue si le total réel dépasse `limit` (re-paginer via `offset` si supporté, ou augmenter `limit` sur les lister_*). Optional sur les tools de listing exhaustif (lister_*).
resultsYesEntrées métier (shape spécifique au tool, cf. description du tool).
query_metadataNoMetadata de la query (radius_km, departement, filtres appliqués, …).
freshnessNoFraîcheur des sources (présent si `include_freshness: true`).
perimetreNoLentille de la source : ce que le comptage inclut/exclut. Lire `completeness_note` et la restituer au lecteur final.
activite_hebergeeNoCompte juxtaposé des sites hébergeant l'activité correspondant à la famille filtrée, sous une autre catégorie FINESS. Distinct du `count` principal — lire `note` pour comprendre la sémantique et ne JAMAIS additionner les deux comptes sans préciser leur nature.
Behavior5/5

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

Annotations already indicate readOnly and idempotent. The description adds rich behavioral context: output compactness, null coords and distance_km (non-spatial), default category (Civil ~97%), opt-in categories with percentages, reference URL, and data source. This goes well beyond annotations and clearly sets expectations.

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 comprehensive but slightly lengthy. It is front-loaded with the main purpose and each sentence adds value. The structure is logical, starting with purpose, then behavioral traits, output details, categories, reference, and source. Could be slightly more concise, but still efficient.

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?

Given the presence of an output schema, the description need not detail return values. It covers coverage, categories, output limitations (null spatial fields), cache staleness, and licensing. However, it omits details about the limit parameter (e.g., default, max) and does not mention any pagination or sorting behavior.

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 coverage is only 20%, so description bears the burden. It explains the role of include_etudiants and include_agents_publics as opt-ins for categories, and mentions include_freshness as an opt-in for freshness metadata. However, it does not describe the limit parameter or expand on num_finess beyond the pattern.

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 verb 'Liste' and the resource 'PS rattachés à un établissement FINESS', and answers the specific question 'qui travaille dans ce labo / hôpital / clinique ?'. It distinguishes itself from siblings by emphasizing its role as a pivot between RPPS and FINESS.

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 gives context for when to use (listing professionals in an establishment) and explains the mode_exercice distinction. It subtly indicates when not to use for spatial queries by directing to etablissement_by_finess for geolocation. However, it does not explicitly list alternative tools or state when to avoid this tool.

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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