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

Annotations already establish that the tool is read-only and closed-world. The description adds important data-quality behavior: certain headline fields are under review and return null, and a review object carries the layer window end as the data date. That is useful transparency beyond annotations, though it does not fully describe response structure.

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 two sentences and front-loads what the snapshot contains. The second sentence carries the necessary null-return caveat and review-object context; dense but free of filler.

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?

With no output schema and no parameters, the description needs to carry the return-value burden. It lists the coverage dimensions, identifies which fields return null, and explains the review object, which is sufficient for a zero-parameter summary tool, though the full response shape is not detailed.

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 tool has zero parameters, so there is no parameter semantics for the description to explain. Under the scoring rule, zero parameters establishes a baseline of 4.

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 gives a clear verb and resource: a one-call snapshot of Voidly's measurement coverage. It enumerates the included dimensions, so the agent understands what the tool returns. It does not explicitly contrast itself with sibling tools such as get_category_coverage or get_measurement_freshness, 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?

The phrase 'One-call snapshot' implies this is for overview use rather than detailed per-category or freshness queries. However, it never names alternatives or states when not to use it, leaving routing to the many sibling tools implicit.

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