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NeuralVerge Business Intelligence

Romania company

run_ro_companies

Get one company from the Romania registry data (Ministry of Finance / ONRC) by CUI (CIF): name, status and registration date, address, trade register number, authorization act, phone/fax, tax registrations (profit tax, VAT, social contributions, ...) and the latest filed financial indicators (assets, debts, equity, turnover, profit, employees). 15 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesCUI (CIF). e.g. 2816464

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it usefully discloses the billing cost ('15 point per returned record') and the breadth of returned data, which is real behavioral context. However it is silent on failure behavior (unknown CUI, invalid format), latency, or whether a missing record returns empty vs. error.

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?

Front-loaded with the verb and resource, then a compact field inventory and a cost note. The long field list is dense but earns its place given there is no output schema; no filler sentences.

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?

Because there is no output schema and no annotations, the enumerated return fields and the per-record cost are exactly the context an agent needs before calling. The only gap is not describing not-found/error handling, which is a minor omission for a single-record lookup.

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

Parameters3/5

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

Schema description coverage is 100% and there is a single parameter already documented as 'CUI (CIF). e.g. 2816464'. The description only restates the same identifier terminology, adding no format, validation, or fallback guidance beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource ('Get one company from the Romania registry data ... by CUI (CIF)') and enumerates exactly what is returned, from name/status/address to tax registrations and financial indicators. The singular 'one company ... by CUI' implicitly but clearly distinguishes it from the sibling run_ro_companies_search, which does bulk lookup.

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 (look up a single Romanian company when you already know its CUI), but never states when to use this versus run_ro_companies_search or what to do if the CUI is unknown. No exclusions or prerequisites are given, so the agent must infer the routing.

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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