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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the bar is lower. The description adds valuable process detail: it probes each entity with ai_visibility_check, ranks by score, and returns a structured result with score, confidence, and signal density. This goes beyond the annotation claims and gives agents a clear mental model of what happens.

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 a clear front-loaded purpose. The second sentence explains mechanics (probing with ai_visibility_check, ranking, surfacing) and the third provides a practical use case and return format. No word is wasted, and every sentence earns its place.

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 moderate complexity and full schema coverage, the description covers the core purpose, process, return structure, and typical use case. The only omission is the entity count range (2-8) and model requirements, but these are already in the schema descriptions, so the description remains sufficient for an agent to invoke correctly. A 4 is appropriate because it does not explicitly state limits, but the schema fills that gap.

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 baseline is 3. The description does not add meaning beyond the schema; it only implies entities are compared, but the schema already documents the 'entities' parameter including the first-as-subject convention. Models, _apiKey, and context are fully described in the schema, so the description does not need to compensate.

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: 'Compare AI visibility across multiple entities side-by-side.' It names the specific verb-resource pair and distinguishes itself from sibling ai_visibility_check by focusing on multi-entity comparison rather than single-entity probing. The phrase 'ranks by score, surfaces which is most/least recognized' further clarifies the unique output.

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 for when to use the tool: 'Useful for competitive AI-marketing audits' and gives an illustrative query. It implicitly distinguishes from ai_visibility_check by describing this as the multi-entity version, but it does not explicitly name alternatives or exclusion criteria. This is a minor gap, so not a 5.

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