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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds the content scope (the metric set) but says nothing about aggregation behavior, date-range defaults, or whether engines/categories narrow or broaden the result — modest value beyond the annotations.

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?

A single sentence with the resource stated first and the metric list after the colon; no filler and nothing wasted.

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 analytics tool with no output schema, naming the returned metrics is genuinely useful, but with six undocumented parameters (including two required and two enum-filtered arrays) and no usage routing, the definition leaves real gaps an agent would need to close by guessing.

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 0% across six parameters, so the description carries the full burden — yet it mentions no parameter at all. It never explains that projectId/siteId are required scope, nor what 'from'/'to' do, nor how the engines and categories filters shape the result.

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 gives a clear verb ('Read') plus the resource ('how often AI assistants mention the brand') and enumerates the metrics returned: visibility, share of voice, position, trend. That is enough to distinguish it from metric siblings like get_ai_visibility_citations or get_ai_sentiment_overview, though it never names those alternatives explicitly.

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?

There is no statement of when to use this tool versus the many adjacent AI-visibility siblings (get_ai_visibility_competitors, get_ai_visibility_domain_pages, get_ai_response, get_ai_sentiment_overview). The agent must infer from the name alone which overview to call.

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