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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is covered. The description adds process and output details: it probes each entity, ranks by score, and returns a ranked list with score, confidence, and signal density. This goes beyond the annotations, though it omits rate-limit/latency considerations.

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 four sentences, each adding distinct value: core purpose, process, use case with an example quote, and return format. It is front-loaded with the purpose in the first sentence and contains no filler.

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?

For a moderately complex tool with 4 parameters, no output schema, but strong schema descriptions and annotations, the description covers why to use it, how it works, and what it returns. It could mention that multiple probes may take time or that an API key is needed for certain models, but the schema already handles the API key detail, so the description is largely complete.

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?

Because schema description coverage is 100%, the baseline is 3. The schema already provides detailed descriptions for all parameters, including entities ('first entry treated as the subject') and models ('workers-ai' default, 'anthropic' requires _apiKey). The description adds no new parameter meaning beyond what the schema already explains.

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 'Compare AI visibility across multiple entities side-by-side,' which is a specific verb+resource combination. It further distinguishes itself from the sibling ai_visibility_check by stating that it probes each entity with that tool and ranks the results, making it clear this is the multi-entity aggregation tool.

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: 'Useful for competitive AI-marketing audits' with an example query. It implicitly references ai_visibility_check for single-entity probes, but does not explicitly say 'use that instead for one entity.' Thus, there is clear context but no explicit exclusions.

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