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

Annotations already cover read-only, idempotent, open-world, non-destructive semantics, so the bar is lower. The description adds genuine behavioral context beyond them: the monthly update cadence, the data-lag consequence (falling back to an earlier month), and a billing note (usage-based, ~$0.012 estimate).

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 core purpose is front-loaded in the first sentence, and the October/September example usefully illustrates the lag concept. The trailing pricing block and a stray leading whitespace character add minor noise but do not obscure the meaning.

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 zero parameters and an output schema present, the description need not describe return values. It supplies the conceptual model (data freshness/lag) an agent needs to interpret the result, leaving only explicit routing guidance as a gap.

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 takes zero parameters, so per the rubric the baseline is 4. There is nothing parameter-wise for the description to document or compensate for.

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 purpose: determining whether Google has refreshed Google Ads keyword data for the prior month. It conveys the verb (check/learn status) and resource (GAds keyword data freshness) clearly. It does not explicitly differentiate itself from sibling freshness/inventory tools, but the concept is unambiguous.

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?

Usage is only implied — an agent infers it should call this before relying on GAds keyword data to know how current it is. There is no explicit when-to-use, when-not-to-use, or named alternative among the many sibling endpoints.

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