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NeuralVerge Business Intelligence

Austria company

run_at_companies

Get one company from the Austria registry (Firmenbuch) by registration number (FN) or registry URL: name, status, legal form, address, previous names and the paid extracts offered. Flat 5 points per successful run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesRegistration number (FN) or registry URL. e.g. 56247t

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 does add genuinely useful behavioral detail: the flat 5-point cost per successful run and the note that paid extracts are offered. However, it says nothing about failure behavior, whether a missing FN errors or returns empty, or any auth/rate constraints.

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 core action and identifier, followed by the returned fields and cost. Two sentences, no padding; the cost sentence earns its place by informing budget-aware agents, though the field list is somewhat compressed.

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 description usefully enumerates the returned fields (name, status, legal form, address, previous names, extracts), which is exactly what the agent needs. It is only slightly incomplete on error/empty-result behavior for an unknown FN.

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 the single 'company' parameter is already documented as 'Registration number (FN) or registry URL. e.g. 56247t'. The description restates the same semantics, so the baseline 3 applies with no added value.

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 (Get), resource (one company from the Austria Firmenbuch registry), and the accepted identifier (FN or registry URL). This clearly separates it from the sibling run_at_companies_search, which handles lookup-by-name rather than a direct single-record fetch.

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 phrase 'Get one company ... by registration number (FN) or registry URL' implies the usage context (you already have an identifier), but the description never names the alternative search tool or states explicitly when not to use this one. Usage is inferable but not spelled out.

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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