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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral details: it probes each entity with ai_visibility_check, ranks by score, treats the first entity as the 'subject' for narrative, and returns a ranked list with score, confidence, and signal density. This goes beyond the annotations without contradicting them, though it doesn't mention rate limits or potential failures.

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 concise and front-loaded with the primary purpose. Four sentences deliver the action, the mechanism, a use case, and the return format without waste. Every sentence earns its place.

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 read-only comparison tool with full schema coverage and detailed annotations, the description provides all necessary context: what it does, how it works, when to use it, and what it returns. The absence of an output schema is compensated by the explicit statement of return fields. It is complete for an agent to select and invoke correctly.

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?

The input schema already has 100% description coverage for all parameters, so the baseline is 3. The description adds extra meaning by explaining that the first entity in the 'entities' array is treated as the subject for narrative, which is not in the schema. This lifts the score to 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 a specific verb ('Compare'), identifies the resource ('AI visibility'), and distinguishes itself from the sibling tool ai_visibility_check by focusing on multi-entity comparison. It also provides a concrete use case example, making its purpose unmistakable.

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 clear context for when to use the tool: 'Useful for competitive AI-marketing audits' with an example question. It does not explicitly name alternatives or exclusions, but the multi-entity focus implicitly differentiates it from single-entity tools. The guidance is strong but could benefit from an explicit 'use this instead of ai_visibility_check for multiple entities.'

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