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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint as false. The description adds value by explaining the internal process: 'Probes each entity with ai_visibility_check, ranks by score, surfaces which is most/least recognized.' It also describes the output structure. This is consistent with annotations and provides sufficient behavioral context beyond what annotations offer.

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 four sentences, each earning its place: purpose, mechanism, use-case, output. It is front-loaded with the main action and avoids unnecessary details. No fluff or redundancy.

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 tool's complexity (multiple entities, optional models, API keys, and context), the description covers how it works (calling ai_visibility_check), what it returns (ranked list with score, confidence, signal density), and when to use it. Combined with rich annotations (readOnly, idempotent) and full schema coverage, the description leaves no significant gaps for an AI agent.

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 input schema already explains all parameters. The description adds context such as the first entity being the 'subject' for narrative, but this is also present in the schema description. The example usage is helpful but does not significantly enhance understanding beyond the schema. Thus, a baseline score of 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 clearly states the tool's purpose: 'Compare AI visibility across multiple entities side-by-side.' It specifies the verb (compare), the resource (AI visibility of entities), and distinguishes itself from siblings like ai_visibility_check (single entity) by emphasizing multiple entities. The use-case example 'does Claude know about us as well as our competitors?' further clarifies its role in competitive audits.

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 provides clear context: it is for comparing multiple entities in competitive AI-marketing audits. It implies that ai_visibility_check would be used for single-entity checks, and the phrase 'Compare... multiple entities side-by-side' indicates when to use this tool. However, it does not explicitly state when not to use it or mention alternative tools like compare_entities, which is a minor gap.

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