AI Search: Get Prompts by Brand (SE Ranking)

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. The description only states the action and endpoint, omitting details about authorization, rate limits, error behavior, or what happens when the brand is not found. A simple fetch operation still warrants mentioning pagination nuances or data freshness.

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 efficiently conveys the core purpose and endpoint. No redundant information. Ideal conciseness.

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?

With 15 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the return format, pagination behavior beyond limit/offset, or how to interpret results. Users would need external documentation for effective use.

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% description coverage, so each parameter is already well-documented. The description adds only the endpoint mapping and pagination context ('paginated list'), which is marginal. Given the baseline of 3 for high schema coverage, this score is appropriate.

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 action ('Fetch a paginated list of prompts'), the resource ('prompts where the specified brand is mentioned in LLM results'), and provides the endpoint. This effectively distinguishes it from siblings like 'aiSearchPromptsByTarget' or 'aiSearchOverview'.

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 brand-specific prompt searches but does not explicitly state when to use this tool versus alternatives (e.g., 'aiSearchPromptsByTarget') or provide context on prerequisites or complementary tools. No when-not-to-use guidance is given.

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