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

The description goes beyond the annotations by explaining the internal process: it delegates to ai_visibility_check per entity, ranks by score, and surfaces which entity is most/least recognized. It also discloses output structure (ranked list with score, confidence, signal density). No contradiction with the readOnlyHint and idempotentHint annotations.

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 sentences, front-loaded with the purpose, followed by method, use case, and return value. Every sentence earns its place—no fluff or repetition of schema or annotation content.

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?

Despite lacking an output schema, the description specifies the return format (ranked list with score, confidence, signal density). It also names the underlying tool (ai_visibility_check) and mentions the optional context parameter's purpose, making the tool's behavior fully comprehensible for an 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 coverage is 100% with clear descriptions for all four parameters. The description adds only a slight semantic overlays (e.g., treating the first entity as 'your brand' and others as competitors), but that is already encoded in the schema ('First entry treated as the "subject"'). Thus description does not add significant parameter meaning beyond the schema.

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+resource: 'Compare AI visibility across multiple entities side-by-side.' It clearly distinguishes from siblings like ai_visibility_check (single-entity) and compare_entities (generic comparison) by focusing on AI visibility and multi-entity ranking.

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 clear context for competitive AI-marketing audits and an example question. It mentions probing each entity with ai_visibility_check, implying this is the multi-entity version of that tool, but it does not explicitly state when not to use it (e.g., for single entities).

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