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

Annotations already cover read-only, non-destructive, open-world. Beyond those, the description discloses the returned field set (LEI, legal name, jurisdiction, status, city/country) and, importantly, the data-completeness limitation that most entities report nothing. It does not mention pagination or limits on the children list, but that is a minor omission.

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?

Three sentences, front-loaded with the dataset name and scope, then the return fields, then the coverage caveat. Nothing is redundant and every sentence carries information an agent can act on.

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 single-parameter read tool with no output schema, the description supplies the return-field inventory and the key expectation that many entities have no reported relationships. That is enough for an agent to call it correctly and interpret an empty result.

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?

There is one parameter at 100% schema coverage, with the schema already documenting the 20-character format and an example. The description restates '20-character LEI' but adds no new semantics, so the baseline 3 is appropriate.

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 names a specific dataset (GLEIF Level 2 'who owns whom'), a specific resource (a 20-character LEI), and the exact scope (direct parent, ultimate parent, direct children). That scope cleanly separates it from lei_lookup/lei_search, which cover entity identity rather than ownership chain.

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?

Usage is clear from 'Reveals the accountable ownership chain behind an entity', and the caveat that only GLEIF-reported relationships come back — 'many entities report none' — is an effective when-not signal. It stops short of naming an alternative tool or stating what to do when no relationships exist.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.