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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds behavioral value by disclosing it probes with ai_visibility_check, ranks by score, and returns a ranked list with specific fields (score, confidence, signal density), which goes beyond 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 with no filler: it states the main action, the method (probing with ai_visibility_check), a concrete use case, and the output shape. Every sentence contributes meaning, and the core comparison action is front-loaded in the first sentence.

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 having no output schema, the description explicitly states the return format ('ranked list with score, confidence, signal density per entity'), which gives the agent a clear expectation. It omits details like model selection and API key nuances, but those are captured in the input schema, making the description sufficient for an initial understanding.

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 all parameters are already well-explained in the input schema. The description adds no new parameter-level details; it only paraphrases the 'entities' concept ('your brand + N competitors') without introducing semantics 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 further distinguishes itself from the sibling ai_visibility_check by stating it probes each entity with that tool and ranks by score, making the comparative scope clear.

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 with 'Useful for competitive AI-marketing audits' and gives a concrete question example. It does not explicitly exclude alternatives, but the reference to 'with ai_visibility_check' implies the single-entity case belongs to that sibling tool, making the usage context clear.

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