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

Annotations declare it is a non-read-only, open-world operation, but the description adds crucial behavioral context the annotations cannot: it runs asynchronously as a background job that must be polled via get_job, requires an active subscription, and its results are meant for user review before tracking. The write/approval workflow is well disclosed.

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 sentences, each earning its place: the action, the excludeQueries nuance, the follow-up workflow, and the subscription prerequisite. The core verb is front-loaded.

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, the description needn't explain returns, and it covers the async workflow and subscription gate well. The main residual gap is the undocumented country/language/org/project parameters, but the agent has enough to invoke it correctly.

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 only 14% (just requestId), so the description must carry more burden. It does clarify the 'input' seed semantics and that excludeQueries leaves out already-tracked queries, but country, language, organizationId, and projectId receive no explanation anywhere. Partial compensation for a low-coverage 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 gives a specific verb and resource ('Start a background job that proposes search keywords for a project') and clarifies the input seed types (topic, product, URL). It is clearly distinguishable from siblings like discover_brands and discover_prompts without opening any schema.

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 lays out the full workflow: poll get_job for the result, review with the user, then track via create_tracked_queries, plus the prerequisite 'Requires an active subscription.' It does not explicitly contrast when to prefer this over discover_brands/discover_prompts, so it stops short of full when-not guidance.

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