Who owns whom, from the official GLEIF LEI graph (CC0 licensed, covers 2.5M+ legal entities worldwide). Query: ?lei=5493001KJTIIGC8Y1R12. Four GLEIF lookups in one call: entity name and status, declared direct parent, ultimate parent, plus the total count and a 10-entity sample of direct children. Unknown LEI returns found=false. 24h cache. Price: $0.005 USDC per call (x402).
| Name | Required | Description | Default |
|---|---|---|---|
| lei | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers key behaviors: it reveals the data source (GLEIF), coverage (2.5M+ entities), caching (24h), pricing ($0.005/call), and behavior for unknown LEI (returns found=false). No contradictions.
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 sentences with no wasted words. The first sentence conveys the core purpose, and the second provides all necessary details. It is appropriately sized and front-loaded.
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 single required parameter, no output schema, and the complexity of ownership data, the description is complete. It covers what the tool returns (four lookups), edge cases (unknown LEI), and operational details (cache, price).
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 coverage is 0%, but the description compensates by explaining the 'lei' parameter with an example query ('?lei=5493001KJTIIGC8Y1R12') and implying it is a Legal Entity Identifier. This adds meaning beyond the raw 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 'Who owns whom' and enumerates four specific lookups (entity name/status, direct parent, ultimate parent, children count/sample), making the tool's purpose crystal clear. It also distinguishes from sibling tools like lookup_lei by focusing on ownership hierarchy.
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 implies usage for ownership queries with a sample query, but does not explicitly compare to siblings or state when to avoid this tool. It provides a concrete example, making it easy to understand the context, but lacks explicit alternative guidance.
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 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.
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.
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.
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.