breakdown

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

Annotations already cover the read-only, non-destructive safety profile. The description adds no further behavioral context such as aggregation method, time-range behavior, sorting, or rate limits.

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?

A single front-loaded sentence with no filler; the dimension list is compact and directly useful.

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?

Output schema and annotations cover return format and safety, and the dimension list helps invocation. However, the definition lacks usage guidance and does not clarify time-range or limit semantics, leaving avoidable ambiguity for a 3-parameter analytics tool.

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?

With 0% schema coverage, the description compensates for the key dimension parameter by enumerating valid values (path, referrer, etc.). It leaves days and limit undocumented, though their titles and defaults make them somewhat inferable.

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?

Describes the operation as returning top values for a dimension and lists the valid dimensions, making the core resource clear. It does not distinguish itself from sibling list_dimension_values, so it falls short of a 5.

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?

No guidance on when to use this tool versus list_dimension_values, query_metrics, or other analytics siblings. The description only states output content, leaving selection to inference.

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