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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds meaningful context beyond that: the aggregation grain, the impression-share metric, and a freshness caveat ('recent ~3 days may be incomplete') that an agent would otherwise not know.

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 tightly packed sentences, front-loaded with the core purpose, then grain/freshness, then the exclusion and alternative. No filler; every clause adds routing or behavioral value.

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, return values needn't be explained, and annotations cover the safety profile. The description covers grain, scope boundaries, freshness, and alternatives, leaving only minor gaps (e.g., pagination behavior is in the schema, not here).

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; every parameter (sort_by, limit, offset, date fields, filters) is documented in the schema. The description adds the notion of grain and metric set but no syntax or format detail for the parameters themselves.

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 (Returns) and resource (bidded Sponsored Products keyword/target performance), plus the exact grain (keyword/target + campaign/ad group). It explicitly distinguishes itself from query-level siblings by naming get_search_terms and get_search_query_performance, so an agent can route 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?

Gives an explicit negative boundary ('Does not include actual customer search queries or market-wide query volume') and routes to two named alternatives. This is strong when-not guidance, though it doesn't contrast against the other performance-granularity siblings (campaign/ad group) by name.

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