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Validate UK VAT Number (HMRC)

vat_validate
Read-onlyIdempotent

Validate a UK VAT number against the HMRC register to retrieve the registered trading name and address for due diligence checks.

Instructions

Validate a UK VAT number against the HMRC register.

Returns the trading name and address as registered with HMRC for VAT purposes. The VAT-registered trading address often differs from the Companies House registered address — that discrepancy is a due diligence signal worth noting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vat_numberYesUK VAT registration number. Accepts: 'GB123456789', '123456789', 'GB 123 456 789'. GB prefix and spaces normalised automatically.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
validYesTrue if HMRC confirmed the VAT number is currently registered. False means HMRC returned 404 (not registered / deregistered).
vat_numberYesCanonical VAT number in 'GB<9 digits>' format.
trading_nameNoTrading name registered with HMRC for VAT. Compare with the Companies House name — discrepancies are a due diligence signal.
registered_addressNoVAT-registered trading address. May differ from the Companies House registered office address.
consultation_numberNoHMRC consultation reference number for this lookup.
Behavior4/5

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

Annotations already indicate read-only (readOnlyHint=true, destructiveHint=false, idempotentHint=true). The description adds behavioral context: returns trading name and address, and notes discrepancy signal, which is useful beyond annotations.

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?

Three sentences, front-loaded with purpose, no unnecessary words. Efficiently structured with a clear first sentence describing the core function.

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?

Despite low complexity, the description covers purpose, input formats, and return information. With output schema available, explanation of return values is sufficient.

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?

Schema coverage is 100% with one parameter. Description adds value by listing accepted formats and noting automatic normalization, which agents may not infer from schema alone.

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 'Validate a UK VAT number against the HMRC register', specifying both the action and resource. It distinguishes from sibling tools like company_profile by focusing on VAT validation.

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 implicitly tells when to use (for VAT validation) but does not explicitly state when not to use or provide alternatives. It is clear enough for a dedicated tool.

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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