search_terms

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

Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds value by revealing that results are real user search queries, include metrics, and indicate whether each term is already a keyword or a negative. This goes beyond the annotations and helps the agent understand the nature of the data returned.

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, tightly worded sentence. It front-loads the core definition ('real search queries that triggered your ads') and ends with the practical purpose. There is no filler or repetition, making it easy to scan and quickly understand.

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 description effectively conveys the tool's role and the nature of its data, but it does not address parameter semantics or how to choose between filters like date_range, only_unadded, or min_impressions. Since an output schema exists, return values are covered, but the agent still lacks guidance on parameter selection and how to translate the results into negative keyword decisions.

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 0%, and the description does not explain any of the 8 parameters. Parameter names like only_unadded and min_impressions are somewhat intuitive, but the description never clarifies their behavior, filtering logic, or how they relate to the returned data. The tool description leaves parameter understanding entirely to the schema titles and defaults.

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 defines the resource as 'real search queries that triggered your ads,' which distinguishes it from keyword-performance or suggestion tools. It also states the data content (metrics, keyword/negative status) and the primary use case (negative keyword decisions), making it easy for an agent to know exactly what this tool provides.

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 strong usage context by labeling this as 'the primary source for negative keyword decisions.' However, it does not explicitly name alternative tools or state when not to use it, so the guidance is clear but lacks explicit exclusions or comparisons to siblings like keyword_performance or suggest_keywords.

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