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NeuralVerge Business Intelligence

Luxembourg company

run_lu_companies

Get one company from the Luxembourg registry (LBR / RCS) by RCS number or registry link: name, status (radiée / en faillite), registration and deletion date, address, legal form, trade names, NACE code, and EUID. 5 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesRCS number or registry URL. e.g. B82454

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
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 does disclose a real behavioral trait – the cost model ('5 point per returned record') – and enumerates the returned fields. It says nothing about auth requirements, behavior on an unknown/ambiguous RCS number, or rate limits, leaving notable gaps for an unannotated tool.

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?

A single sentence that front-loads the verb, scope, and identifier, then compresses the return payload into a tight list. No filler and nothing buried.

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, the field enumeration (name, status, dates, address, legal form, trade names, NACE, EUID) usefully describes the return, and the cost note is a bonus. Error/not-found handling and identifier format edge cases are the only real omissions for a 1-param 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 coverage is 100% and the single parameter already documents 'RCS number or registry URL' with an example. The description restates the same dual input form without adding format rules, so 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?

Specific verb ('Get one company') plus resource ('Luxembourg registry LBR/RCS') and an explicit input discriminator (RCS number or registry link). Listing the returned fields further pins down what this tool does versus the sibling run_lu_companies_search, which is a list/search tool.

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 phrasing 'by RCS number or registry link' implies the prerequisite (you must already know the identifier), which suggests when to reach for this versus a search tool. However, it never names run_lu_companies_search or states the when-not condition, 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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