Search Analytics (performance) query

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

Annotations already indicate read-only, idempotent, and open-world behavior. The description adds valuable behavioral context beyond annotations: 2-3 day data lag, inclusive Pacific Time dates, pagination behavior (no page token, loop until empty), long-tail data anonymization, and the 1,200 qpm quota. No contradiction with annotations.

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 every sentence carries useful information. It opens with the core purpose, then progressively details output, date semantics, pagination, data caveats, and quota. No filler or repetition; the structure front-loads the most important information and then covers edge cases.

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?

This is a 10-parameter tool with no output schema, so the description must explain both request nuances and return shape. It covers row structure, sorting, pagination, dimension effects, data lag, and quota. Combined with the 100% schema coverage, the agent has everything needed to invoke and interpret results correctly.

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?

Even though schema descriptions cover 100% of parameters, the description adds semantic depth: explains keys[] ordering, ctr fraction, inclusive end_date, pagination with start_row/row_limit, why data_state 'all' matters, and the grouping caveat that summed rows won't match totals. These clarifications go well beyond schema property descriptions.

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 the tool's function: 'Runs a Search Analytics (performance) query for a property' with specific metrics (clicks, impressions, CTR, position) and grouping by dimensions. It distinguishes itself from siblings like list_sites or get_top_queries by focusing on the full analytics query capability, and even explains output row structure.

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 provides rich usage context: how to get a totals row (no dimensions), pagination via start_row/row_limit, data_state selection for fresh data, and the caveat about anonymized data when grouping by query/page. However, it does not explicitly mention when to choose this tool over alternatives like get_top_queries, so it stops short of full 'when-not' guidance.

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