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NeuralVerge Business Intelligence

Czech Republic company

run_cz_companies

Get one company from the Czech Republic commercial register (Justice.cz) by registration number (IČO, 8 digits) or registry URL: name, status, registration date, address and court file number. Also returns legal form, business scope, share capital, officers, shareholders and branches. 5 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesIČO or registry URL. e.g. 45274649

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
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 pricing ('5 point per returned record') and enumerates the returned data, but says nothing about authentication, rate limits, or error behavior for an invalid IČO/URL.

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?

Three sentences, front-loaded with the identifier format before the returned-fields list and the cost note. The field enumeration is somewhat long but every item is informative, so little 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, the description must describe return values, and it does list them (name, status, registration date, address, court file number, legal form, business scope, share capital, officers, shareholders, branches) plus cost. Only error/edge-case behavior is missing.

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?

The single parameter is already fully documented in the schema (IČO or registry URL, example 45274649). The description restates the same information with the added detail that IČO is 8 digits, which is mildly useful but mostly redundant at 100% schema coverage.

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 Czech Republic commercial register (Justice.cz)') and names the exact lookup keys (IČO 8 digits or registry URL). This clearly distinguishes it from the sibling run_cz_companies_search, which would be name-based discovery.

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

Usage Guidelines4/5

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

The description tells the agent what input is required (a registration number or registry URL), which implicitly tells it when this tool applies versus a search. However, it never explicitly names run_cz_companies_search or states when NOT to use this tool, so the routing is inferred rather than 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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