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kimhjort

aria-mcp-cvr-dk

by kimhjort

lookup_company

Look up Danish companies in CVR by CVR number, company name, or phone number to identify businesses from invoices or contracts.

Instructions

Look up a Danish company in CVR (Det Centrale Virksomhedsregister) by CVR number, company name, or phone number. Returns structured fields: cvr, name, address, zipcode, city, phone, email, industry_code, industry_description, company_type, active status, start_date, end_date, employees, credit_bankrupt. Use this when you need to identify a company from an invoice, email, or contract, e.g. "hvem er CVR 12345678" or "find Netcompany". Data source: cvrapi.dk (free tier, ~50 lookups/day).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesCompany name, CVR number (8 digits), or phone number to search for.
Behavior5/5

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

No annotations are provided, so the description fully discloses behavior: it states the data source (cvrapi.dk), rate limit (~50 lookups/day), and lists the return fields. This transparency is excellent for a lookup 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?

The description is concise (two sentences) and well-structured. The first sentence states the action and search keys, the second provides usage context and data source. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple nature of the tool, the description covers all necessary aspects: purpose, usage, return fields, data source, and rate limit. No output schema exists, but the description lists the fields, making it complete.

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?

The schema already describes the 'query' parameter, but the description adds valuable meaning by specifying that it can be a company name, CVR number, or phone number, which is not in the schema description.

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?

The description clearly states the action ('Look up'), the resource ('Danish company in CVR'), and the search keys (CVR number, company name, or phone number). It distinguishes itself from the sibling 'search_companies' by being a direct lookup.

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 provides clear when-to-use context: 'Use this when you need to identify a company from an invoice, email, or contract.' It gives concrete examples. It does not explicitly state when not to use, but the context is strong enough to infer.

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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