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

With no annotations, the description carries the full burden and does so: it discloses that links are name matches, not confirmed ownership, that empty results are normal, that limit is applied per kind (newest first) so one kind cannot crowd out the other, and what counts/truncated actually mean. It also states the auth mechanism (X-API-Key header) and plan requirement.

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?

Purpose is front-loaded in the first line, followed by the semantic caveat and then the paging/auth mechanics in a sensible order. Slightly verbose — the sentence explaining that commercial names identify businesses while trademarks distinguish goods/services is interpretive gloss rather than operational guidance, though it does help interpret output.

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?

There is no output schema, and the description compensates by explaining the counts and truncated response fields and how to react to truncation (raise limit). Combined with plan/auth disclosure and the name-match caveat, an agent has everything needed to call and interpret this correctly.

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?

Schema coverage is 100%, so the baseline is 3; the description goes beyond it by clarifying that limit is applied independently to each kind and ordered newest-first, and by identifying where the required company slug comes from. It adds no detail on the 1-200 bound, which lives only in 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?

States a specific verb and resource ('Trademarks and trading names linked to one company') and pins the direction of the lookup ('by name (slug from company_history)' / 'which trading names and trademarks does the patent office list under a holder of this company's name'), which is enough to separate it from the inverse sibling brand_owner. It also defines what each of the two result kinds means.

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?

Gives clear context for when results will be empty ('An empty result is ordinary — most companies have neither on file') and states the plan prerequisite for calling it. It stops short of naming alternatives — notably brand_owner, which is the reverse lookup and the most likely source of confusion — so it lacks explicit exclusions.

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