Skip to main content
Glama

get_company_details

Fiche détaillée d'une entreprise ou d'un établissement français (base SIRENE). Un seul identifiant, deux usages : un SIRET (14 chiffres) renvoie la fiche de CET établissement ; un SIREN (9 chiffres) renvoie celle du SIÈGE de l'entreprise. Structure de la réponse : la racine décrit l'ÉTABLISSEMENT (adresse, activité, effectif, état, conventions collectives applicables à CE site) et le bloc unite_legale décrit l'ENTREPRISE (identité, dirigeants, chiffre d'affaires, TVA). Le niveau de détail dépend du plan : géolocalisation et TVA en Starter, dirigeants et conventions collectives en Growth, finances et procédures collectives en Business. Un champ ABSENT n'est pas une donnée inexistante : il peut être hors plan — propose alors la montée de plan plutôt que d'affirmer que la donnée n'existe pas. Les dirigeants sont des données personnelles issues du Registre National des Entreprises (INPI) ; chacun porte opposition_prospectiontrue = cette personne s'est opposée à l'usage de ses données à des fins de prospection commerciale, false = pas d'opposition enregistrée, null = non renseigné (à ne pas lire comme false). C'est le SEUL endroit où cette information est servie. Plan minimum : Discovery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_idYes

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It thoroughly covers response structure (root vs unite_legale), plan-dependent field availability, the caveat that absent fields may be out-of-plan, and the semantics of opposition_prospection including the distinction between null and false. This is exemplary transparency for a data retrieval 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?

The description is relatively long but information-dense. It is logically structured: identifier usage, response layout, plan tiers, field absence semantics, and a privacy flag caveat. Every sentence adds value, though a bit more concision could improve scannability.

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?

Despite lacking an output schema, the description provides a complete picture: what the response contains, how it varies by plan, how to interpret absent fields, and where special data (opposition_prospection) is served. It successfully covers all key contextual aspects for a tool with a single parameter and no structured output metadata.

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

Parameters5/5

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

The schema only provides company_id as a string with 0% description coverage. The description compensates completely by explaining that the same identifier accepts either a 14-digit SIRET (returns that establishment) or a 9-digit SIREN (returns the headquarters), adding precise meaning beyond the schema.

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 tool provides a detailed record of a French company or establishment (SIRENE base). It goes beyond a simple identifier by explaining the dual SIRET/SIREN usage, and its focus on retrieving detailed records distinguishes it from sibling search tools like search_company.

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 when to use the tool: when you have a SIRET or SIREN identifier. It also explains the plan-level constraints and the meaning of the input. However, it does not explicitly mention alternatives (e.g., use search_company if you lack an identifier), so it falls short of a 5.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct operation: search, verify, nearby lookup, company details, routing, matrix, etc. The descriptions explicitly cross-reference similar tools (e.g., 'préfère route_matrix' for bulk distances, 'préfère verify_address' for confirmation), making the boundaries clear.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern (search_address, get_company_details, verify_address). The exception is 'route_matrix', which is a noun phrase and breaks the pattern, though it remains readable and predictable enough.

Tool Count5/5

With 9 tools, the set is well-scoped within the ideal range. Each tool provides a meaningful capability without overlap or redundancy, covering address, company, routing, and locality data.

Completeness5/5

The server covers the core read-only workflows for its domain: address search/verification/nearby, company search/details, route calculation/matrix, and locality search/list. No obvious gaps or dead ends exist for a data lookup service.