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

With no annotations, the description carries the full burden and does so excellently. It discloses that it uses model training knowledge rather than live lookup, that figures are estimates, the pay-per-call cost and payment mechanism, and the error behavior when the payment-signature header is missing. All of this is beyond what structured data would provide.

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 efficiently structured and every sentence adds unique information: purpose, usage context, data limitations, alternative tool, pricing, and error handling. No fluff or redundancy.

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 tool with no output schema, the description informs the agent about the return value (top 10 keywords with relative search volume and difficulty), data freshness, pricing, and failure modes. This is complete for a 2-parameter tool.

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 baseline is 3. The description does not add meaning beyond the schema for the two parameters; it refers to 'a topic' which aligns with the 'query' description but adds no new semantics for 'context'.

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: 'Suggest the top 10 SEO keywords for a topic' with 'estimated relative search volume and difficulty.' It also distinguishes itself from siblings by naming generate-content-calendar for posting schedules and by describing its use case for early keyword ideation.

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 explicitly provides usage context: 'Use for early keyword ideation and content planning,' and names an alternative for a different scenario: 'For a posting schedule, use generate-content-calendar.' It also cautions that this is not live keyword-tool data and advises validation before budget commitment.

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