EU company registry lookup across 16 countries incl. Sweden Bolagsverket.
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Average 4.3/5 across 3 of 3 tools scored.
The three tools have clearly distinct primary functions: get_company by national ID, lookup_company_by_vat by VAT number, and search_company by name. Some overlap exists on VAT lookups for certain countries, but descriptions clarify the differences.
All tool names follow a consistent verb_noun pattern: get_company, lookup_company_by_vat, search_company. The verbs are semantically appropriate for retrieval operations, and the casing is uniform.
Three tools is on the smaller side, but it is appropriate for a specialized registry lookup server. Each tool covers a distinct query method, so none feels superfluous or redundant.
The server covers the core lookup operations by ID, VAT, and name for supported European registries. Minor gaps exist, such as no separate LEI-specific lookup or batch operations, but the described surface addresses the primary use cases.
get_companyAGet a non-Czech company by national ID and country code. Supported: gb (CRN), sk (IČO), pl (KRS number), nl/it/at/es/be/lt (VAT via VIES), de (LEI), fr (SIREN), no (organization number), dk (CVR number), fi (Business ID), ee (registry code), se (10-digit organisation number via Bolagsverket).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | National company ID, e.g. UK Companies House CRN "14356670". | |
| country | Yes | ISO alpha-2 code or supported country name. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context about the data sources and identifier types per country (e.g., VIES, Bolagsverket), which goes beyond the readOnlyHint. It also explicitly limits the scope to non-Czech companies. There is no contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single punchy sentence followed by a compact list. It front-loads the core purpose and then efficiently enumerates supported countries without redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter lookup tool, the description is comprehensive: it covers all supported countries, identifier types, and sources. Annotations handle read-only and open-world semantics, so the description does not need to detail return values or error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with examples, so the baseline is 3. The description enhances this by mapping each supported country to its expected identifier format (e.g., gb -> CRN, pl -> KRS), which is critical for constructing valid 'id' values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: retrieving a non-Czech company using an ID and country code. It distinguishes itself from sibling tools by listing the specific country-ID mappings, making the exact scope and method unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool (when you have a national ID and country code for a non-Czech company) and enumerates supported countries and identifier formats. It does not explicitly name alternatives or exclusions, but the high specificity implies the appropriate use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup_company_by_vatAFree VIES VAT lookup. Returns VAT validity plus name/address when the member state discloses them; some countries such as ES/DE may return only validity.
| Name | Required | Description | Default |
|---|---|---|---|
| vat | Yes | EU VAT number including ISO-2 country prefix, e.g. "NL123456789B01". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and openWorldHint=true, and the description adds valuable behavioral context that some countries (ES/DE) may only return validity, not name/address. This goes beyond the annotation hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences immediately convey purpose and a key caveat. Every word earns its place, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description explains what is returned (validity, optional name/address) and notes country-specific limitations. It does not detail the exact response structure, but this is sufficient for a simple read-only lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single 'vat' parameter with a format example. The description adds no additional parameter semantics, so the baseline of 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states this is a VAT lookup tool for EU VAT numbers, and it returns validity plus available company details. It distinguishes from sibling tools by focusing specifically on VAT-based lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus get_company or search_company. It implies a use case (VAT lookup) but provides no guidance on alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_companyASearch non-Czech business registries by company name. Supported: GB (Companies House), SK (ORSR/RPO), PL (KRS), NL/IT/AT/ES/BE/LT (GLEIF/LEI only; exact VAT data via lookup_company_by_vat or get_company with VAT), DE (GLEIF/LEI), FR (SIRENE), NO (BRREG), DK (CVR), FI (PRH YTJ), EE (RIK open data), SE (GLEIF/LEI name search; use get_company for full Bolagsverket data).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Company name or partial company name. | |
| limit | No | Max results per search, default 10, max 20. | |
| country | No | ISO alpha-2 code or supported country name, e.g. "GB", "UK", or "United Kingdom". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful context beyond readOnlyHint/openWorldHint by disclosing that some countries only have GLEIF/LEI data and directing to alternatives for fuller records. It stops short of describing pagination, rate limits, or result shape.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a dense single sentence that front-loads the core action and packs country specifics into a compact list. It is slightly long but every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's multi-country scope and simple annotations, the description is largely complete: it specifies supported countries, data source limitations, and alternatives. It lacks any mention of the response format or pagination, which would be useful with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters, so baseline is 3. The description elevates country semantics by mapping each country to its data source and giving examples, which helps the agent select valid inputs. It omits unspecified country default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search non-Czech business registries by company name' and enumerates supported countries with their specific registries, which distinguishes it from siblings like get_company and lookup_company_by_vat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly names alternatives for exact VAT data (lookup_company_by_vat or get_company with VAT) and for SE full data (get_company), telling the agent when not to use this tool. The 'non-Czech' qualifier also sets clear boundaries.
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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