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

Annotations only declare read-only, open-world, non-destructive behavior, so the description carries the substantive disclosure: anonymized queries are dropped by Google at query level causing 30-40% lower clicks, the response carries a `source` field of 'google' vs archive, and older archive ranges include a `note` about excluded anonymized traffic. This is exactly the kind of caveat an agent needs to interpret results correctly.

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 opening lines front-load purpose and return shape, and the bulleted enumeration of the three sourcing cases is well structured. It is on the long side with some connective prose ('This tool handles that as follows') that could be trimmed, but nearly every sentence carries decision-relevant information.

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?

For a tool with an output schema, seven parameters, and a subtle data-provenance problem, the definition covers the sourcing rules, the freshness tradeoff, and the alternative tool. Nothing needed to call it or to interpret its results is missing.

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 coverage is 100%, so the baseline is 3; the description goes beyond it by explaining that the 'query' dimension or a query filter changes the data source, and that no dimensions or only 'date' yields totals including anonymized traffic. It does not add anything about row_limit/start_row pagination semantics, so it falls short of a full 5.

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?

States a specific verb and resource ('Query the Personal Archive'), names the scope beyond Google's 16-month limit, and specifies that it returns aggregated rows by requested dimensions with impression-weighted position. It is clearly differentiated from the sibling search_analytics_query, which it names directly.

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?

Explicit routing rules are given: use for historical/trend questions where freshness is not critical, and use search_analytics_query for the last 3 days. It also enumerates exactly which requests are served from archived rows, which from archived daily totals, and which are proxied live to Google.

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