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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the selection criteria and purpose; it does not mention that the tool is read-only, how it handles missing optional parameters, whether it returns metrics like impressions/CTR/position, or any constraints such as data availability. The description adds no behavioral context beyond the core filter logic, which is insufficient for a tool with no annotations.

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 a single, efficient sentence that front-loads the core selection criteria (ranking 5-20, high impressions, low CTR) and immediately states the practical value. There is no wasted wording; it is concise and well-structured for quick parsing by an agent.

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?

The tool has 6 optional parameters with full schema documentation, so parameter handling is covered. The description explains the purpose and selection logic, which is sufficient for an agent to decide when to call it. However, there is no output schema, and the description does not mention what fields are returned (e.g., query, impressions, CTR, position), which could be assumed but is not explicit. This minor gap prevents a perfect score.

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?

The schema has 100% coverage with detailed descriptions for all six parameters (days, site, limit, end_date, start_date, min_impressions), including defaults and constraints. The tool description does not mention any parameters, so it adds no extra semantic meaning beyond the schema. Baseline 3 is appropriate because the schema already documents the parameters adequately.

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 clearly states the tool finds queries ranked 5-20 with high impressions but CTR below typical for their position, explicitly framing it as where title/snippet rewrites are most valuable. This is a specific verb (queries/finds), a resource (queries), and a distinct selection criterion that differentiates it from siblings like 'top' or 'page_queries' without needing to inspect them.

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 gives a clear use case: identifying optimization opportunities for title/snippet rewrites. It implies when to use the tool (when the agent needs queries to improve CTR) but does not explicitly mention alternatives or when not to use it. The context is strong enough for an agent to decide, but it lacks explicit routing to other tools like 'top' or 'page_queries'.

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