Get Keyword Suggestions

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

With no annotations, the description carries the behavioral burden. It discloses that output is an autocomplete proxy for keyword volume, not actual volume, and that it should be combined with search-term reports for conversion insight. This is useful non-obvious behavioral context, though it doesn't discuss rate limits or auth.

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?

Two short paragraphs with the core purpose in the first sentence; the second adds valuable context about what the suggestions represent and how to use them. No filler or repetition.

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 and all parameters described, the description covers the essential usage context. It could add a note on when not to use it, but it is complete enough for an agent to invoke 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 description coverage is 100%, so the parameters are already documented fully. The description doesn't add any extra meaning beyond 'keyword' as the seed term.

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 ('get') and resource ('keyword suggestions'), and explains they are Play's autocomplete suggestions — the terms users actually type. This clearly distinguishes it from sibling tools like get_search_terms and search_store.

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?

Explicitly recommends pairing with get_search_terms to see which suggested terms converted, giving clear complementary usage context. It doesn't state explicit exclusions, but the main use case is unambiguous.

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