search_term_harvest

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

With no annotations, the description must independently disclose behavior. It reveals the tool processes search queries and generates suggestions tied to ad groups, adding useful context. Yet, it does not clarify whether this is read-only, what data sources are used, or how 'exact keyword' is determined, leaving notable transparency gaps.

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 concise, using only two sentences to convey the core purpose. The 'growth mirror' phrase is efficient but slightly cryptic; overall, it earns its place without unnecessary verbosity.

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?

Given that the tool has four parameters and no schema-level descriptions, the description is insufficient for understanding parameter semantics or proper usage. The presence of an output schema helps with return values, but the lack of parameter guidance and usage boundaries makes the overall description incomplete for effective tool invocation.

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 input schema has zero description coverage, and the tool description provides no explanation of parameters such as limit, lookback, or min_conversions. This is a critical deficiency for an agent to correctly invoke the tool with appropriate values, especially since the schema only offers names and default values.

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 identifies the tool's function: converting non-exact search queries into keyword suggestions with ad group context. The phrase 'growth mirror of find_wasted_spend' differentiates it from the sibling tool, establishing a clear purpose. However, the verb 'converting' could be more specific about the exact output (e.g., 'generates suggestions'), leaving slight ambiguity.

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 implies usage context by positioning the tool as the 'growth mirror' of find_wasted_spend, suggesting it is for expansion rather than waste reduction. However, it lacks explicit guidance on when to use this versus alternatives like add_keywords or list_keywords, leaving the agent to infer the appropriate context.

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