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

Annotations already establish the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), so the bar is lower, yet the description adds genuinely useful context beyond them: results are representative samples rather than a complete registry feed, and explicitly not demand measurement, valuation, or investment advice. It also flags the constraint that scope=com is unavailable for prefix, a behavioral limit not visible from annotations alone.

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?

Three dense, front-loaded sentences with no filler; the core purpose leads and the scope caveats follow. Slightly long, but each sentence carries distinct 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?

With an output schema present, return values need no explanation, and annotations carry the safety profile; the description covers parameter meaning and the sampling disclaimer. The only notable gap is the absence of explicit routing guidance against sibling trend/keyword tools.

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 coverage is 100%, so the baseline is 3, but the description goes beyond the thin schema text ('Trend dataset to return') by explaining that hot/emerging represent rolling keyword cohorts and prefix represents prefix activity buckets. That adds real semantic meaning to the enum values rather than restating 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 states a specific verb and resource ('Return provider-computed keyword registration statistics') and explains what the three type values produce, so the agent knows exactly what the tool yields. It does not, however, explicitly contrast itself with near-siblings like keyword_data or tld_trends, leaving that differentiation implicit.

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 clarifies what each type and scope value covers ('hot and emerging cover rolling keyword cohorts; prefix returns prefix activity buckets'), which implicitly guides selection among the enum values. It gives no explicit when-to-use or when-not-to-use guidance relative to alternative tools such as keyword_data or tld_trends.

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