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

With no annotations provided, the description carries the behavioral burden and does so well: it explains that terms are deduplicated per ad group (implicit segmentation), that zero-impression terms are omitted by Google, and that ad_account_id must be a bare 10-digit ID. This meaningfully discloses quirks 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?

Every sentence earns its place: the core definition, the optimization use case, deduplication behavior, Google's omission quirk, and the account ID format. It is dense but well organized and front-loads the most important identification details.

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 is complete for a report tool with no output schema: it names the metrics, explains result segmentation and omission behavior, and documents the key parameter constraint. It could explicitly state the return wrapper/type, but an agent has enough context to invoke it 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 schema already documents all six parameters thoroughly. The description adds modest value by reinforcing ad_account_id format and explaining segmentation/omission behavior tied to the data, but it does not substantially expand per-parameter meaning beyond the schema.

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 states a specific verb and resource: fetching the search terms report for a Google Ads account. It clearly distinguishes the data type ('REAL user queries') from other report/insight tools and explains what metrics are included, so an agent can understand exactly what this tool returns.

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 provides strong context for when to use it: the 'classic optimization read' for finding irrelevant queries to negate and high-converting queries to add as exact keywords. It does not explicitly name sibling alternatives or exclusion conditions, but the use case guidance is concrete enough to guide selection.

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