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

Annotations already establish read-only, non-destructive, and non-open-world behavior. The description adds no behavioral traits beyond that, such as pagination, ordering, date-range limits, or whether results are complete or sampled.

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 single sentence is front-loaded and free of filler. It is appropriately concise, though its extreme brevity leaves necessary operational details to be inferred.

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?

Given the complexity of seven parameters, three required IDs, date filters, and engine filters, the description is incomplete. It does not explain required inputs or filtering behavior, and no output schema exists to offload return-value documentation.

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 0% and the description mentions no parameter names or meanings. With seven parameters, including required IDs and date/engine filters, the description fails entirely to compensate for the missing schema documentation.

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 ('List') and resource ('recorded answers for one prompt across AI engines'), which clearly separates it from list_ai_visibility_prompts and run_ai_visibility_prompt. It does not explicitly name alternatives, but the resource distinction is sufficient for an agent to identify its 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?

No when-to-use guidance, prerequisites, or comparison to sibling tools is provided. The description implies a historical review use case but does not state when this tool is preferable to get_ai_response or list_ai_visibility_prompts.

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