google_ads_validate_query

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 disclosure. It usefully reveals that the tool checks segment restrictions and resource availability and implies it does not execute the query itself. However, it does not describe the return format, failure behavior, or whether it performs any I/O, which leaves important behavioral 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 a single, front-loaded sentence with no filler. Every phrase contributes meaning: what it validates, the timing, and the specific checks performed.

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 only three parameters and no nested objects, so the description is largely adequate for calling it. However, there is no output schema and the description does not state what the tool returns (e.g., boolean, list of errors, or throwing an exception), leaving an important gap for the agent.

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 describes metrics and dimensions, but resource only has a default value. The description adds relational meaning by tying metrics, dimensions, and resource together into a compatibility check, which is not obvious from the schema alone. It does not enumerate valid keys or segment restriction details, but it compensates for the moderate schema coverage.

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 uses a specific verb ('Validate') and a clear object ('metric/dimension/resource compatibility'), and the qualifier 'BEFORE executing a query' distinguishes this from execution-oriented siblings like google_ads_run_gaql. An agent can immediately tell this is a pre-flight validation tool rather than a query runner.

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 clearly frames when to use the tool: before executing a query. It also specifies what it checks (segment restrictions, resource availability), giving the agent actionable context. However, it does not explicitly name alternatives or state when NOT to use it, such as when the user actually wants to run the query.

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