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

The description adds behavioral context beyond annotations by revealing that engine count scales with the user's plan (free = 2) and listing the engines scanned. It doesn't mention side effects or rate limits, but annotations already indicate non-destructive behavior, so no contradiction.

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?

Two concise sentences, front-loaded with the main action, with no filler or repetition. Every sentence adds useful information about the two modes and plan-scaling behavior.

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 adequately explains the core behavior, including the decisive city parameter and plan-dependent scaling. However, it does not describe the output format or explicitly differentiate from the sibling audit_brand_visibility, leaving some gaps for a tool with six parameters and no output schema.

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's mention of city passing/omitting partially reflects the schema's own description of the `city` parameter, adding little new parameter-level meaning beyond what the schema already 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 runs an AI visibility scan for a brand, with specific modes (local-business vs multi-engine GEO) and names the engines involved. This specific verb+resource+scope is sufficient to distinguish it from sibling tools like audit_brand_visibility.

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 explicit instructions on when to pass `city` vs omit it, defining two distinct use cases. However, it does not mention alternatives or when not to use this tool compared to siblings such as audit_brand_visibility, so it lacks full exclusion guidance.

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