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NeuralVerge Business Intelligence

Argentina companies search

run_ar_companies_search

Search the Argentina registry of legal entities (Registro Nacional de Sociedades, IGJ) by company name or CUIT: name, CUIT, company type, address, main activity and link. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoStatus. Options: active = Active, inactive = Inactive / dissolved
keywordYesCompany name. e.g. ypf
max_itemsNoMax items (up to 250) Default: 25.
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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 usefully discloses billing behavior ('1 point per returned record') and the read-only nature is implied by 'Search', but it says nothing about rate limits, pagination behavior, or permission requirements.

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?

Two sentences, front-loaded with the verb and resource, and the returned-field list and cost note are compact. Slightly dense with the field enumeration, but nothing is wasted.

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?

With no output schema, listing the returned fields (name, CUIT, type, address, activity, link) and the per-record cost fills important gaps. All four parameters are documented in the schema. Missing only pagination/empty-result behavior, which keeps it short of 5.

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 100%, so the baseline is 3, but the description adds meaning beyond the schema by stating that CUIT can be used as a search key, whereas the keyword schema description only mentions 'Company name'. This is a genuine semantic addition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Search') and resource (Argentina registry of legal entities, naming the Registro Nacional de Sociedades/IGJ), and lists the returned fields. It does not explicitly distinguish itself from the sibling run_ar_companies, so an agent must infer the search-vs-lookup split.

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?

Says the search is performed 'by company name or CUIT', which implies the intended input context, but gives no when-to-use guidance, no exclusions, and no pointer to run_ar_companies for single-entity retrieval. Usage is implied rather than stated.

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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