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

Annotations already indicate readOnly, openWorld, idempotent, non-destructive. The description adds value by detailing that it probes each entity with 'ai_visibility_check', ranks by score, and returns a ranked list with score, confidence, signal density. It also notes the first entity is treated as the 'subject' for narrative, which is beyond annotation coverage.

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 two concise sentences that cover purpose, method, and use case. It is front-loaded with the primary action. However, it could be slightly more structured (e.g., bullet points for return fields) to improve readability, but it is efficient and not verbose.

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 description explains the return format (ranked list with score, confidence, signal density) despite no output schema. It also mentions the sub-tool invocation. However, it does not explicitly restate the entity count limit (2-8) from the schema, but that is captured in the parameter description. Overall, it provides sufficient context for correct tool usage.

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 baseline is 3. The description adds useful context: it clarifies that the 'context' parameter disambiguates common names and that the first 'entities' entry is the subject with others as competitors. This enhances understanding beyond the schema alone.

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 explicitly states 'Compare AI visibility across multiple entities side-by-side', which clearly identifies the verb (compare) and resource (AI visibility). It distinguishes from the sibling tool 'ai_visibility_check' which checks a single entity, and from generic 'compare_entities' by specifying AI presence context.

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 notes it is 'Useful for competitive AI-marketing audits' and provides an example question, implying when to use. While it does not explicitly state when not to use or name alternatives, the sibling tool 'ai_visibility_check' suggests single-entity cases, and the context is clear enough for an agent to infer appropriate usage.

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