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

Annotations already claim read-only, idempotent, open-world, non-destructive behavior. The description adds that it probes each entity with ai_visibility_check, ranks by score, and returns a ranked list with score/confidence/signal density. This provides useful context for how the tool operates without contradicting the 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?

The description is three sentences, front-loaded with the action and differentiated purpose. Each sentence provides distinct value: method, use case, and output format. The quoted example is concise and helpful, not wasteful.

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 compensates by specifying the return structure (ranked list with score, confidence, signal density). Parameters are fully covered by schema, and annotations cover safety. It could mention rate limits or auth details, but the schema already covers the _apiKey parameter, making this sufficient.

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% and each parameter has detailed descriptions, so the baseline is 3. The description does not add significant parameter meaning beyond echoing the entities concept, while the schema already explains first-entry-as-subject and model/API key constraints.

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 function with a specific verb ('Compare'), a specific resource ('AI visibility across multiple entities'), and explicitly distinguishes from the sibling ai_visibility_check by indicating it probes each entity and ranks by score. The tool's purpose is 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 a clear use case for competitive AI-marketing audits and explicitly contrasts with ai_visibility_check by describing how it probes each entity. However, it does not mention alternatives such as compare_entities or state when not to use the tool, so it lacks explicit exclusions.

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