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lei_ownership

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).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leiYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It discloses: official GLEIF source, CC0 licensing, geographic coverage (2.5M+ entities), query format, unknown LEI behavior (found=false), caching (24h), and pricing (x402). It does not mention rate limits or auth, but for a simple lookup tool this level of detail is strong.

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?

The description is compact and information-dense, with the core purpose front-loaded ('Who owns whom') and supporting details efficiently ordered. Every sentence contributes: data source/coverage, query example, return contents, unknown behavior, and pricing. No wasted words.

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?

For a single-parameter tool with no output schema or annotations, the description covers all essential aspects: input format, output scope, edge cases, data provenance, caching, and cost. It is sufficiently complete for an agent to select and invoke this tool without needing additional context.

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?

The only parameter, lei, has zero description in the schema, so the description must compensate. It provides a concrete query example (?lei=5493001KJTIIGC8Y1R12) that demonstrates the expected format. It doesn't explicitly state the LEI standard length or validation rules, but the example gives an agent enough grounding to fill the parameter correctly.

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 uses a clear, specific framing ('Who owns whom, from the official GLEIF LEI graph') and enumerates exactly what the tool returns: entity name/status, direct parent, ultimate parent, and direct children sample. This distinguishes it from sibling tools like lookup_lei, which likely handles only basic LEI lookup.

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 implies when to use this tool—when you need ownership hierarchy and parent/child relationships from GLEIF—and highlights that it consolidates 'four GLEIF lookups in one call.' It does not explicitly name alternative tools or exclusion criteria, but the context is clear enough for an agent to choose it over simpler LEI lookups.

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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