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

Beyond the annotations, the description discloses important behavior: pricing, x402 payment handling via _meta, exclusion and charging for keywords without data, and the distinction between free bad input and charged upstream errors. These details materially affect whether and how an agent should invoke the tool.

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 dense but front-loaded: the core capability and use case come first, followed by metric definitions, charging rules, and payment mechanics. Every sentence contributes operationally relevant information.

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 paid, external-data tool with no output schema, the description covers the essential context: what metrics are returned, bulk limits, missing-data behavior, billing semantics, and the x402 payment mechanism. The schema already handles location, language, and fallback details.

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 the parameters are already well documented. The description adds useful semantics for returned metrics, but it adds little input-parameter meaning beyond what the schema already provides, so the baseline of 3 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 states a specific resource and metric set: search volume, CPC, competition, keyword difficulty and search intent for up to 100 keywords. It also implies a clear use case that separates it from idea-generation siblings, but it does not explicitly name or contrast a sibling such as keyword_search_volume.

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 gives a clear usage condition: 'Use when you already have a keyword list to prioritise.' That helps distinguish it from keyword_ideas, but there is no explicit when-not guidance or named alternative tool.

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