gsc_search_analytics

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context beyond annotations, such as the return format (JSON rows with metrics and dimension keys, total row count metadata), defaults (end_date defaults to today, row_limit defaults to 100), and the requirement for a verified property. No contradictions 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 well-structured with a concise summary line followed by an Args section and Returns section. It is front-loaded with the core purpose, and every sentence adds value. The length is appropriate for the tool's complexity, with no wasted words.

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?

The description covers the essential aspects of the tool: data returned, grouping dimensions, filtering, date range, pagination, and search type. It explains the return format and metadata. Although an output schema exists, the description still provides the necessary high-level overview. For a tool with this many options, the description is thorough and complete.

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 0% at the top level, but the description compensates by enumerating all parameters with their types, optionality, and defaults. It adds meaning beyond the schema by explaining each parameter's purpose (e.g., pagination offset, search type options). The nested schema also has detailed descriptions, so the description supplements rather than duplicates.

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 it queries search performance data (clicks, impressions, CTR, position) for a verified property, distinguishing it from sibling tools that handle sites, URL inspection, and sitemaps. The verb 'query' and resource 'search analytics data' are specific and 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?

The description provides clear context for when to use the tool (to retrieve search analytics with grouping/filtering). It doesn't explicitly mention when not to use it or name alternatives, but the distinct purpose among siblings makes its usage obvious. No exclusions are stated, but the context alone is sufficient.

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