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Glama

search_company

Recherche des entreprises et des établissements français dans la base SIRENE (INSEE), par nom, SIREN, SIRET, ville, code postal, code NAF, ou par proximité géographique. IMPORTANT : un résultat est TOUJOURS un ÉTABLISSEMENT (un SIRET), jamais une entreprise — même groupé par entreprise, où le SIREN est représenté par son meilleur établissement (le siège de préférence). Ne dis donc pas « 3 entreprises trouvées » pour 3 établissements d'un même SIREN. Par défaut, un résultat par entreprise si query est fourni, un résultat par établissement en recherche par proximité ou par siren ; force ce comportement avec group_by_company. Lis classement_pertinence avant de présenter un « meilleur match » : à false (listing simple ou tri par distance), le premier résultat n'est PAS le plus probable. Un résultat diffusible: false a ses nom et adresse masqués par l'INSEE — c'est la loi, pas une donnée manquante : ne complète jamais de mémoire. Une liste vide fait autorité : aucune entreprise ne correspond. La fiche complète s'obtient ensuite via get_company_details. Plan minimum : Discovery — la recherche par proximité (lat/lon/radius_m) nécessite le plan Growth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNo
lonNo
cityNo
pageNo
queryNo
sirenNo
statusNo
addressNo
naf_codeNo
per_pageNo
radius_mNo
postal_codeNo
group_by_companyNo

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description bears full responsibility and excels: it discloses that results are always SIRET, explains grouping behavior, warns about 'classement_pertinence' affecting best match, clarifies that 'diffusible: false' is legal masking not missing data, and specifies plan restrictions. 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?

The description is packed with useful information in a single paragraph, but lacks visual structure (e.g., bullet points). However, every sentence adds value, and it is front-loaded with the main purpose. Could be slightly more concise, but overall effective.

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 complexity (13 params, no output schema, no annotations), the description covers essential behavioral aspects and usage nuances. It explains the establishment-vs-company subtlety, result ordering, data masking, and plan requirements. It does not describe the response format, which would be helpful given no output schema, but remains fairly complete for the tool's intended 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 0%, so the description must compensate. It lists and explains many parameters (query, siren, city, postal_code, naf_code, lat/lon/radius_m, group_by_company) and their effects on behavior. However, it does not systematically cover all 13 parameters (e.g., page, per_page, status, address are not explicitly described), leaving some gaps.

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 'Recherche' and resource 'entreprises et établissements français dans la base SIRENE', listing multiple search criteria. It distinguishes from sibling tools like get_company_details by mentioning it as the next step, and implicitly differentiates from other search tools by focusing on company data.

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 provides explicit when-to-use guidance, including that results are always establishments, how grouping works, interpretation of 'classement_pertinence', handling of 'diffusible: false', the authority of empty lists, and plan requirements for proximity search. It directs to use get_company_details for more details.

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

A4.4/5.0
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.