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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it probes each entity with ai_visibility_check, ranks by score, and returns a ranked list with score, confidence, and signal density. It does not mention potential rate limits or auth implications, but these are partially covered in the schema.

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 concise and well-structured: four sentences cover purpose, mechanism, use case, and return value. It is front-loaded with the action, and every sentence earns its place without redundancy or fluff.

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 tool with 4 parameters and no output schema, the description provides a solid overview: what it does, how it works (probes with ai_visibility_check), when to use it, and what it returns (ranked list with score/confidence/signal density). It lacks explicit alternative references or limitations, but the schema and annotations fill the remaining gaps effectively.

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%, with all four parameters described in the input schema. The description reinforces the 'entities' parameter as 'your brand + N competitors' but does not add any new parameter-level semantics beyond what the schema already provides. Baseline 3 is appropriate.

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 specific verb and resource: 'Compare AI visibility across multiple entities side-by-side.' It clearly distinguishes itself from the sibling tool ai_visibility_check by emphasizing the multi-entity comparison and competitive aspect, making its purpose unambiguous.

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 an explicit use case: 'Useful for competitive AI-marketing audits' with an example question, which clearly signals when to use the tool. It does not explicitly state when not to use it or name alternatives, but the multi-entity framing versus the single-entity sibling ai_visibility_check implies the distinction.

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