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

The description adds valuable behavioral context beyond annotations: it discloses that results are 'representative samples, not a complete registry feed, demand measurement, valuation, or investment recommendation.' It also warns that scope=com is not available for prefix, which is a non-obvious constraint. This complements the readOnly/idempotent annotations well.

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 three sentences, each earning its place: purpose, type/scope semantics, and caveat. It is well-structured, front-loaded with the main action, and contains no redundant or filler text.

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?

Given the tool's moderate complexity (2 enum params, output schema present), the description fully covers what the tool does, the meaning of each parameter, and important limitations. The output schema handles return format details, so nothing else 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?

Although schema descriptions cover 100% of parameters, the tool description enriches them significantly. It explains that 'hot' and 'emerging' cover rolling keyword cohorts, while 'prefix' returns prefix activity buckets, and further details the difference between scope=all and scope=com including availability restrictions. This adds real meaning beyond the enum lists.

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 opens with a specific verb and resource: 'Return provider-computed keyword registration statistics.' It clearly distinguishes itself from sibling tools by focusing on keyword trends (vs. tld_trends, keyword_data) and explains the three data types (hot, emerging, prefix) with enough specificity to orient the agent.

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 provides clear context for when to use the tool by explaining the meaning of each type and scope option. It doesn't explicitly name alternative tools or exclusion scenarios, but the information given is sufficient for an agent to decide when this tool is appropriate.

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