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

Annotations already declare read-only, open-world, non-destructive behavior, and the description goes beyond them with cost information ('1 DidYouSEO AI credit per call; a failed lookup is refunded') and a hard result cap of 50. It does not, however, cover pagination or latency for the open-world lookup.

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 short sentences, front-loaded with what the tool returns before the use case and the cost caveat. Every sentence earns its place with no 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?

With no output schema, the description compensates by naming the returned fields, the result limit, and the sort order, plus the credit cost. An agent has everything needed to call 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 100% and the single 'seed' parameter is documented with an example in the schema itself, so the schema carries the parameter burden. The description only restates 'seed phrase' without adding format, matching, or length semantics.

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?

States a specific verb and resource ('Get ... keyword ideas that contain a seed phrase') plus the exact output contents (search volume, keyword difficulty) and ordering (sorted by volume). It does not explicitly distinguish itself from the close sibling get_keyword_data, so it falls short of a 5.

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?

Gives a concrete use case: 'Use it to find low-difficulty keywords a new page can rank for.' That is clear positive guidance, but there is no statement of when not to use it or which sibling to prefer for other keyword needs.

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