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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds valuable behavioral context: it probes each entity with ai_visibility_check, ranks results, and returns a specific structure (score, confidence, signal density). This goes beyond the structured annotations, though it doesn't disclose potential rate limits or multi-probe latency.

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 three sentences long, front-loaded with the main purpose, and includes a practical example. Every sentence adds value, and there is no redundant repetition of schema information or annotations.

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 is well-specified: schema covers all parameters, annotations cover safety/behavior, and the description explains the return format in the absence of an output schema. It lacks only minor details such as error handling or rate limits, but for a read-only comparison tool, the description is sufficiently 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?

Schema description coverage is 100%, so the baseline is 3. The description adds meaningful semantics by explaining that the entities array should contain 'your brand + N competitors' and that the first entry is treated as the 'subject' for narrative. It also clarifies the optional context parameter's purpose, which enriches what the schema alone provides.

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 compares AI visibility across multiple entities side-by-side, using a specific verb ('Compare') and resource ('AI visibility'). It also distinguishes itself from sibling tools by explicitly mentioning it probes entities with ai_visibility_check, indicating it's a multi-entity wrapper.

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 clear usage context for competitive AI-marketing audits and gives a concrete example question. It mentions the underlying tool (ai_visibility_check), implying when a single-entity check would suffice, but it does not explicitly say 'use this instead of X' or list when not to use it.

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