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Glama

buscar_empresas

Busca empresas argentinas por razón social y/o filtros combinables (forma legal, jurisdicción, ciudad, actividad, estado fiscal, rango de capital y sellos booleanos como importador/exportador/empleador/contratista) sobre un padrón de ~1,3M de empresas. Devuelve hasta 50 resultados por página con el total. Cuesta 1 crédito por página.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNobúsqueda textual por razón social
pepNotrue = solo empresas con el sello "Vinculada a funcionario (PEP)"
apocNotrue = solo empresas con el sello "En base APOC"
ciudadNo
paginaNo
repsalNotrue = solo empresas con el sello "Sanciones laborales (REPSAL)"
capitalNorango de capital del último balance: lt-1m | 1m-10m | 10m-100m | gt-100m
actividadNocódigo de actividad AFIP
empleadorNotrue = solo empresas con el sello "Empleadora"
deuda_bcraNotrue = solo empresas con el sello "Con deuda BCRA"
exportadorNotrue = solo empresas con el sello "Exportadora"
importadorNotrue = solo empresas con el sello "Importadora"
sancionadaNotrue = solo empresas con el sello "Sancionada (UIF/CNV/BCRA)"
contratistaNotrue = solo empresas con el sello "Contratista del Estado"
forma_legalNosa, srl, sas, cooperativa, fundacion…
jurisdiccionNoprovincia o 'Ciudad Autónoma de Buenos Aires'
estado_fiscalNoactiva | inactiva | baja | suspendida | unknown
cheque_rechazadoNotrue = solo empresas con el sello "Con cheques rechazados"
concurso_quiebraNotrue = solo empresas con el sello "En concurso o quiebra"

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses pagination behavior ('Devuelve hasta 50 resultados por página con el total') and credit cost ('Cuesta 1 crédito por página'), which are useful operational traits. However, it does not discuss authentication, error handling, or confirm read-only nature, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three short sentences, front-loaded with the core purpose. Every sentence provides valuable information: search scope, filter options, and operational details (pagination/cost). No fluff or redundant content.

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?

For a tool with 19 parameters and no output schema, the description provides a solid overview of capabilities, data source (~1.3M companies), and response limits. It lacks details on return fields and error scenarios, but the schema covers parameter specifics, so the description is sufficiently complete for a search tool.

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 high (89%), so the baseline is 3. The description adds meaning by explaining filters are 'combinables' and enumerates categories (forma legal, jurisdicción, etc.), which clarifies that multiple parameters can be used together. This goes beyond the individual parameter descriptions in 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 verb 'Busca' (searches) and the resource 'empresas' (Argentine companies), listing specific filter categories. It distinguishes this tool from siblings like buscar_dirigentes and ficha_empresa by focusing on general company search with combinable filters.

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

Usage Guidelines3/5

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

The description implies usage for searching companies by name and filters, but it does not explicitly state when to use this tool versus alternatives like buscar_importadores or ficha_empresa. There is no mention of exclusions or alternative selection, only the tool's own capability.

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

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct entity or action: searches for people, companies, importers, and tenders are clearly separated, as are company and person detailed profiles, credit balance, and autocomplete. The two overlapping-looking tools (buscar_empresas and sugerencias) differ in purpose: full search vs. lightweight autocomplete, so no real ambiguity exists.

Naming Consistency4/5

Tool names follow a clear pattern: buscares use verb_noun, fichas use noun_noun, and saldo_creditos/sugerencias are standalone nouns. This is mostly consistent and predictable, with minor deviation from a strict verb_noun pattern.

Tool Count5/5

With 8 tools, the server is well-scoped for its purpose of retrieving Argentine business data. It covers multiple search domains, detailed profiles, account management, and autocomplete without excessive fragmentation or unnecessary tools.

Completeness4/5

The core domain is well covered: search for companies, people, importers, and tenders, plus detailed profiles for companies and people. A minor gap is the lack of detail views for individual importers or tenders beyond search results, but agents can typically work around this with the existing search capabilities.

Resources