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

With no annotations provided, the description carries the full burden and excels. It reveals that unsupported jurisdictions are silently dropped, resulting in a false-empty result with status 'completed' and no error. It also warns about the stale jurisdiction list and directs users to check `jurisdictions_not_searched` and `coverage_warning` in the response—critical behavioral insights beyond what any schema would encode.

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 well-structured and front-loaded: a one-line purpose, followed by necessary usage caveats, then Arg descriptions and examples. Every sentence serves a purpose—no fluff. The length is justified by the five parameters and the critical silent-drop behavior.

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?

The description is remarkably complete for a tool with no annotations. It covers purpose, parameter semantics, edge cases (silent drops, stale jurisdiction list), response fields to verify (`jurisdictions_not_searched`, `coverage_warning`), and includes two examples. The existing output schema complements this well, so the description doesn't need to re-explain return values.

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 input schema has zero descriptions for parameters, so the description's Args section fully compensates. It explains each parameter: name, jurisdictions (required, with example format), include_sanctions_check (default true), include_inactive_roles (default true), and api_key (alternatives via headers). Concrete examples further clarify usage.

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 opens with a clear, specific verb-resource statement: 'Search company registries for a person's directorships, officer roles, and shareholdings.' This distinguishes it from its sibling company_search_company, which presumably searches for companies. It also mentions automatic sanctions screening, further refining the tool's purpose.

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 provides strong usage guidance: jurisdictions are mandatory, 'ALL' is not supported, the list can go stale (call company_registries() for the live list), and XX is a global registry. It gives explicit prerequisites and pitfalls, but it does not explicitly contrast this tool with alternatives like company_search_company. The when-to-use is implied by the person focus.

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