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eu-verify

by io.github.contentfactory

lookup_company_uk

Official UK Companies House data in one paid call. Search: ?q=tesco returns matching companies (number, status, type, incorporation date). Profile: ?number=00445790 returns the full profile PLUS current officers and PSC (persons with significant control, the UK quasi-UBO register): names, roles, natures of control, risk flags (insolvency history, charges, overdue filings) and typed insolvency cases when history exists. Statutory register data, minimized. 24h cache. Price: $0.01 USDC per call (x402).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNo
limitNo
numberNo

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description discloses key behaviors: paid call at $0.01, 24-hour cache, and return of risk flags and insolvency history. It truthfully indicates it is a mutation (paid read) without contradiction.

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?

The description is a single dense paragraph that efficiently conveys key points (modes, data, cost, cache). It front-loads the main verb and resource but uses abbreviations (PSC, quasi-UBO) that may require domain knowledge.

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?

Given no output schema, the description adequately explains return types for both modes, including risk flags and insolvency cases. It covers pricing and cache, though a more structured output description would enhance completeness.

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?

With 0% schema coverage, the description adds meaning by linking q to search, number to profile, and implying limit applies to search results. However, it does not explicitly define limit's role or value bounds, leaving some ambiguity.

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 tool retrieves UK Companies House data with two distinct modes: search by query (q) and profile by company number. It lists specific data returned (status, type, officers, PSC, risk flags), distinguishing it from sibling tools like lookup_company_fr.

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 explains when to use search vs profile ('Search: ?q=tesco' vs 'Profile: ?number=00445790') and mentions pricing and caching. However, it does not explicitly state when not to use the tool or compare it to sibling tools.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool serves a distinct verification or lookup purpose (e.g., company lookup, sanctions screening, address geocoding, IBAN validation) with no overlap. Even tools targeting the same source (e.g., check_eori vs. validate_vat_eu) have clearly different inputs and outputs.

Naming Consistency4/5

Almost all tools follow a verb_noun pattern (verify, validate, lookup, check, find, screen) with clear nouns. The only exception is 'catalog' (a noun-only name), but it's a minor deviation that doesn't cause confusion.

Tool Count5/5

19 tools is appropriate for a data verification service covering company data, sanctions, VAT, addresses, emails, IBANs, and financials. Each tool addresses a specific need without being excessive or sparse.

Completeness5/5

The tool set covers the full lifecycle of EU company verification: existence, status, financials, ownership, VAT, sanctions, EORI, invoices, tenders, and address validation. No obvious gaps for its stated domain.

Resources