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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds useful behavioral context beyond that: it internally calls ai_visibility_check for each entity, ranks results by score, and returns a ranked list with specific fields (score, confidence, signal density). This gives an agent a clear picture of side effects (none) and output structure that annotations do not convey.

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?

Four tightly written sentences, each earning its place. The first sentence states the core action, the second explains the mechanism, the third gives a concrete use case, and the fourth specifies the return fields. No fluff or repetition.

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?

The tool has moderate complexity (multi-entity probing, ranking) and no output schema, so the description compensates by disclosing return fields. It does not mention error handling, rate limits, or how the score is calculated, but given the strong annotations and full schema coverage, this is sufficient for selection and invocation. Slightly more detail on the relationship to ai_visibility_check would have pushed it to 5.

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 4 parameters are fully documented in the schema. The description does not add parameter-level meaning beyond what the schema already states (e.g., 'entities' array, first entry as subject). Baseline 3 is appropriate because the schema carries the burden.

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 and resource: 'Compare AI visibility across multiple entities side-by-side.' It clearly distinguishes itself from single-entity tools by stating it probes each entity and ranks them, and the competitive angle is explicit ('your brand + N competitors'). The example question reinforces the purpose.

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?

Provides clear context: 'Useful for competitive AI-marketing audits' and gives an example use case. It implies this is for multi-entity comparison rather than a single check, but does not explicitly name alternatives or state when not to use it. No exclusions are given, so it earns a 4.

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