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

Beyond the annotations, the description discloses the premium cost model, latency of seconds-to-a-minute, quota sensitivity, and plan-gate constraints per engine. It also clarifies the optional brand-tracking behavior and the GET endpoint. These details materially help an agent decide whether the call is worth making.

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 dense but well-organized: purpose first, then cost/latency cautions, then plan gating, then endpoint. Every sentence adds decision-relevant information, and there is no filler.

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?

With no output schema, the description adequately explains the main return shape (answer_text plus citations and optional brand_visibility). It also covers the key operational constraints: cost, latency, quota, and plan-gated engine availability. Nothing critical for correct invocation appears missing.

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 still adds value by mapping the engine enum to plan tiers and by clarifying that passing brand yields a brand_visibility object, which is not fully captured by the schema descriptions. It does not add further meaning for prompt, country, fields, or additional_prompt beyond what the schema already says.

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 gives a specific verb+resource (send a prompt to an AI answer engine), names the engines, and states the primary return values (answer_text with citations and optional brand visibility). It clearly distinguishes this from the sibling search tools, which cover web, image, video, shopping, etc.

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?

It provides strong usage context: it warns that quota is spent at a premium per-answer rate, that responses are slow, and that it must not be repeated needlessly. It also explains plan gating by engine. However, it does not explicitly name an alternative tool for when a cheaper or faster search is more appropriate.

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