Search Console performance report

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 behavioral context by explaining that it supports grouping, filtering (with an example), and pagination, which goes beyond the annotations. It does not cover rate limits or auth, but the annotations suffice for safety, and the description adds operational details.

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 two sentences, front-loaded with the primary action and metrics. It includes an example for filtering and mentions pagination, all in a compact format. Every sentence contributes useful information without redundancy.

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 complexity (10 parameters, no output schema), the description covers the core use case well: it states the metrics returned, the grouping options, filtering, and pagination. It does not explicitly mention data lag (though that is in the parameter descriptions) or the need to use gsc_list_sites for siteUrl, but these are covered by the schema. Overall, it is fairly complete for an agent to understand the tool's purpose and basic usage.

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 70%, so the schema already documents most parameters. The description adds value by summarizing the grouping dimensions and providing a filtering example (page contains '/blog/'), which helps agents understand how to use the dimensions and filters parameters. It does not repeat schema details but enriches the conceptual model.

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 queries Google Search performance data with specific metrics (clicks, impressions, CTR, average position) and lists the grouping dimensions (query, page, country, device, date, searchAppearance). It also mentions filtering and pagination, which distinguishes it from sibling tools like gsc_compare_periods or gsc_opportunities by focusing on raw data retrieval.

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 gives clear context on what the tool does (query performance data) and its capabilities (filtering, pagination), which implies when to use it. However, it does not explicitly state when not to use it or mention alternatives such as gsc_opportunities or gsc_ctr_opportunities, so there is no explicit exclusion guidance.

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