brand_visibility

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

Annotations only provide readOnlyHint=true; the description adds that it queries multiple AI models with the same prompt and analyzes brand mentions. It does not disclose return format, behavior when brand is omitted, or potential costs/rate limits, so the added context is moderate.

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 well-structured: opening summary, elaboration, usage note, and parameter list. Every sentence adds value without redundancy, and it is appropriately sized for a 3-parameter tool.

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?

It covers core purpose and two main parameters but lacks output format description (no output schema exists) and does not explain the config parameter. Given the complexity of querying multiple AI models, these gaps make it incomplete for a robust understanding.

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?

Since schema coverage is 0%, the description compensates well for prompt and brand with clear explanations and examples. However, it entirely omits the config parameter, and the brand description ('track in responses') is somewhat vague, leaving a notable gap.

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 checks how a brand appears in AI-generated answers from ChatGPT, Claude, and Perplexity. It uses a specific verb ('Check') and defines the resource, distinguishing it from sibling SEO/AEO tools by focusing on brand mentions in AI responses.

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?

It explicitly says 'Use this for Generative Engine Optimization (GEO) analysis,' providing a clear when-to-use context. However, it doesn't mention alternatives or exclusions, so it earns a 4 rather than a 5.

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