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

No annotations are provided, so the description must carry behavioral disclosure. It clearly explains date boundaries, UTC vs. Pacific, partial evidence, and the rule not to call partial data current, nor pad GSC values. This is a rich behavioral contract for the tool.

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 dense but not overly long; it packs essential caveats into a few sentences. It front-loads the core purpose and then adds important accuracy constraints. No fluff, but could be slightly more structured.

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?

Given the single optional parameter and no output schema, the description explains key context: date formats, timezone boundaries, partial coverage, verification states, and GSC limits. An agent has enough information to call it correctly and avoid misrepresenting data.

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% for the only parameter, windowDays, which is well documented in the schema with enum values. The description does not add new meaning about the parameter beyond the schema, so baseline 3 is appropriate.

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 clearly states that the tool returns audit summaries and trends, with specific field semantics. It distinguishes it from related tools like get_audit_findings by focusing on summary-level trends. However, it does not explicitly name a sibling tool as an alternative.

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 implies usage context through coverage and date handling rules, but does not explicitly state when to use this tool versus alternatives. It gives guidance on interpretation (e.g., when isCurrent false), but the when-to-use vs. when-not-to-use is absent.

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