Check AI Visibility Score

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

Annotations already declare the tool as read-only, non-destructive, idempotent, and open-world. The description adds value by specifying the return type (per-model visibility scores) and the specific AI assistants tested, which goes 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?

The description is a single sentence of 20 words, conveying all necessary information without fluff. It is front-loaded with the core action and returns format.

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 simple one-parameter tool with strong annotations and an output schema, the description is complete. It covers purpose, input, and output (per-model scores). No further context is needed.

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 has 100% coverage with a clear description of the 'website_domain' parameter. The description adds context that the domain is checked for AI assistant knowledge/recommendation, enhancing meaning beyond the schema.

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 it tests whether AI assistants (ChatGPT, Perplexity, Gemini) know about and recommend a brand, and returns per-model visibility scores. The verb 'test' and resource 'brand visibility' are specific, and the mention of specific assistants distinguishes it from sibling tools like aipush.analysis.profile.

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 implies usage for checking brand visibility, but does not explicitly state when to use this tool versus alternatives like aipush.analysis.profile or other aipush tools. No guidance on when not to use it or context for selecting it over siblings.

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