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

The description discloses that it probes each entity with ai_visibility_check, ranks by score, surfaces most/least recognized, and returns a ranked list with score, confidence, and signal density. This adds behavioral context beyond the annotations (which already mark it read-only). Minor omission: no mention of time/rate-limit implications of multi-probe orchestration, but the annotated safety profile lowers the bar.

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 concise sentences: the first front-loads the core purpose, the second explains the mechanism and use case, and the third states the output. Every sentence contributes value with zero fluff.

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 tool's complexity (4 params, 1 required, no output schema), the description covers the mechanism, use case, and return format ('ranked list with score, confidence, signal density'). This is sufficient for an agent to select and invoke the tool correctly, especially with fully documented schema and annotations.

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 restates the 'first entry as subject' nuance already present in the entities parameter description. No additional parameter semantics are provided in the tool description.

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 is highly specific: 'Compare AI visibility across multiple entities side-by-side' clearly states the verb, resource, and scope. It also distinguishes from sibling tools by mentioning the internal use of ai_visibility_check and the ranking/surface outcome, making it unique among compare_entities and ai_visibility_check.

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 gives a clear use case ('competitive AI-marketing audits') and an implicit alternative ('Probes each entity with ai_visibility_check' suggests using that tool for single-entity checks). However, it doesn't explicitly state when NOT to use this tool vs. alternatives, so it falls just short of a 5.

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