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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavioral context beyond that: the API is stateless, uses no local/server context, returns only the answer text, and is paid per call. This is useful disclosure for an agent deciding whether to invoke it.

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 short sentences with no filler. The most important trait ('stateless') is front-loaded, and each sentence adds distinct useful information: operation, behavior, return value, and cost.

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 two-parameter tool, the description is complete. It covers what the tool does, its statelessness, its return value, and its cost. No output schema exists, but 'Returns only the answer text' sufficiently describes the response shape for this tool.

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 description coverage is 100%, so the schema fully documents both parameters. The description does not add much parameter-level meaning beyond reinforcing that the question is answered without context, which is acceptable but not a boost above the baseline.

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 verb ('answers') and resource ('the buyer's question with a language model'), and the stateless/no-context phrasing distinguishes it from the sibling tools. An agent can tell this is a standalone generation API rather than a lookup, conversion, or routing tool.

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 implies when to use the tool: for a direct language-model answer with no local or server context. However, it never names alternatives or explicitly says when not to use it, such as when contextual information is required. Usage context is present but only implicit.

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