Look up a Legal Entity Identifier (LEI) in the official GLEIF registry — by 20-char LEI code or company legal name. Returns LEI, registration status, jurisdiction and address country.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | LEI code or company legal name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It states the tool queries an official registry, implying a read-only operation, but it does not explicitly disclose that no modifications occur, nor does it mention any external API dependencies, rate limits, or response characteristics beyond the listed fields. This is adequate for a simple lookup but leaves some behavior implicit.
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?
The description is a single, focused sentence that fronts the core purpose and lists key return fields without extraneous detail. It is efficient and well-structured for an agent to parse quickly, though it could be broken into a bulleted list for even clearer scanning.
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?
For a simple tool with one parameter and no output schema, the description provides a solid picture: the input format, the source (official GLEIF), and the main output fields. It does not cover error cases (e.g., invalid LEI format or no match found), but these are not critical for a basic lookup and the description is adequate for the tool's complexity.
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?
The schema covers 100% of the single parameter, but the description adds meaningful detail by specifying that the LEI must be a 20-character code, which the schema description ('LEI code or company legal name') does not. This extra precision helps agents validate input format and adds value beyond the 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 the verb ('look up'), the specific resource (Legal Entity Identifier in the official GLEIF registry), and the input scope (20-char LEI code or company legal name). It also lists the returned fields, distinguishing it from sibling tools like entity_resolve or kyb_verify_business which target broader business verification.
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?
No guidance is provided about when to choose this tool over alternatives. The description does not mention any alternative tools or exclusions. An agent must infer from the name and context that this is the dedicated LEI lookup, but no explicit when-to-use/when-not-to-use information is given.
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.
Most tools are clearly distinct by resource or function, but fx_rates vs us_treasury_fx and entity_resolve vs lei_lookup could both be plausible choices for the same request. Descriptions generally make the boundaries clear, so the overlap is minor rather than systematic.
All names use lowercase_snake_case, but there is no single naming pattern: tools like btc_network, crypto_price, and weather_forecast are noun phrases, while eu_vat_validate, lei_lookup, and sanctions_screen follow an object+operation style. This mixed convention is readable but noticeably inconsistent.
14 tools is within a reasonable range for a multi-provider data server, and most tools cover a distinct data domain. However, kyb_verify_business heavily overlaps the individual VAT, LEI, sanctions, IBAN, and entity tools, and having two FX rate tools makes the set feel slightly broader than necessary.
The main KYB/entity workflow is well covered, but the set has notable gaps: sanctions screening covers only OFAC and UK OFSi, IBAN validation is structural only, and there are no UBO or adverse-media checks. For the broader data-lookup domain, the coverage is decent but not exhaustive.