validate_eu_vatValidate an EU VAT number against the official EU VIES registry. FREE. Returns whether the number is currently valid and, when the member state discloses it, the registered company name and address. Covers all 27 EU member states.
| Name | Required | Description | Default |
|---|---|---|---|
| vat | Yes | EU VAT number: 2-letter country code + number, e.g. IT08714440016. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description adds useful context: it returns validity and optional company info, is free, covers 27 countries. However, it does not mention side effects, authentication needs, or error conditions, leaving some behavioral gaps.
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?
Three concise sentences, no wasted words, front-loads the action and key attributes (free, coverage).
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?
The description covers the main purpose, input, and output for a simple read tool, but could mention potential errors or limitations (e.g., network dependency, member state disclosure variability).
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 provides 100% coverage with a description of the single parameter; the tool description adds an example format but does not significantly enhance understanding beyond the schema.
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 action ('Validate an EU VAT number') against a specific resource (VIES registry), distinguishes from siblings like list_supported_countries and lookup_eu_company, and adds details about being free and covering all EU member states.
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 for when to use (validating EU VAT numbers) and implies alternatives via sibling tools, but does not explicitly state when not to use or list specific exclusion scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: listing supported countries, looking up a company (with a free jurisdiction detection and a paid full record), and validating EU VAT numbers. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case: list_supported_countries, lookup_eu_company, validate_eu_vat. Easy to predict and read.
Three tools is appropriate for the domain of EU compliance covering VAT validation and company data lookup. Neither too few nor too many.
The set covers key operations: discovering coverage, detecting jurisdiction, and validating VAT. A minor gap is the lack of a tool to directly handle the paid service, but the descriptions guide the user externally.