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NeuralVerge Business Intelligence

LEI Lookup company subsidiaries

run_lei_lookup_company_relationships

Subsidiaries of one legal entity in the LEI register (direct and ultimate children): LEI, name, type of relationship and link. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesLEI or lei-lookup.com link. e.g. 7LTWFZYICNSX8D621K86
max_itemsNoMax items (up to 250) Default: 25.
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It usefully reveals the result shape (LEI, name, relationship type, link) and the pricing model ('1 point per returned record'), which is genuine behavioral context. However, it omits authorization requirements, rate limits, and pagination behavior beyond what the schema fields imply.

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?

Two short sentences, front-loaded with the core purpose and result fields before the cost note. Nothing is padded, though the '1 point per returned record' clause could be seen as slight operational noise rather than invocation-relevant guidance.

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?

With no output schema and no annotations, the description steps in by enumerating the returned fields and the cost per record, which largely compensates. For a three-parameter lookup with full schema coverage, an agent has enough to call it correctly; only auth/rate-limit context is missing.

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?

Schema description coverage is 100%, so all three parameters (company, max_items, start_page) are already documented in the schema with formats and bounds. The description adds no parameter-specific nuance, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: subsidiaries of one legal entity in the LEI register, including direct and ultimate children. It clearly separates itself from entity-fetch tools by scoping to relationships, but it never names a sibling (e.g. run_lei_lookup_companies) to make the choice explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'of one legal entity' implies the prerequisite (you already have a company LEI) and the use case (relationship mapping), but there is no explicit when-to-use statement, no when-not-to-use, and no named alternative among the many run_*_companies siblings.

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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