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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by revealing that it probes each entity via ai_visibility_check, ranks by score, and returns a structured output. This explains the underlying mechanism and output behavior without contradicting the read-only hint.

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 serving a purpose: main function, mechanics, use case, and output. It is front-loaded and free of fluff. Every sentence adds value, making it appropriately concise for the tool's complexity.

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 (meta-tool invoking another tool, ranking, output structure) and lack of output schema, the description covers the essential aspects: it states the return format ('ranked list with score, confidence, signal density per entity') and provides a concrete usage scenario. It does not explain ranking metric nuances, but the provided information is sufficient for most invocation contexts.

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 coverage is 100%, so the baseline is 3. The description adds extra meaning to the 'entities' parameter by stating 'First entry treated as the "subject" for narrative; rest are competitors.' This clarifies the role of the first entity, which is not evident from the schema alone, justifying a 4.

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 uses specific verbs (compare, probes, ranks, surfaces) and uniquely identifies the resource (AI visibility). It distinguishes from sibling tools by explicitly referencing ai_visibility_check and emphasizing multi-entity comparison, making it distinct from the single-entity counterpart.

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 a clear use case: 'Useful for competitive AI-marketing audits' with an example query. This gives the agent context on when to deploy the tool. However, it does not explicitly contrast with alternatives like ai_visibility_check or state when not to use it, so it stops 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.