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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description adds genuine behavioral detail beyond that by disclosing the return shape (totals, click share, top non-brand queries), which matters because there is no output schema.

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?

Three short sentences with zero filler; the core operation is front-loaded and the regex example and return summary follow in order of usefulness.

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 read-only, idempotent analysis tool with no output schema, the description covers the operation and the main return values adequately. The only notable gap is the undocumented days and compare parameters, which the agent must infer.

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 only 50%: property and brandPattern are documented, but days and compare are described in neither schema nor description. The inline regex example ('metric ?port|metricport') usefully clarifies the brandPattern format, so the description adds real value even though it leaves two parameters unexplained.

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 ('splits queries into brand and non-brand') and is clearly distinct from siblings like gsc_top_queries, gsc_query_clusters, or gsc_search_analytics, none of which perform a brand/non-brand segmentation. An agent can identify the tool's job without opening the schema.

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 never says when to reach for this tool versus the other GSC query tools, nor any prerequisites or exclusions. The line 'Non-brand is the real SEO performance' hints at motivation but is framing, not actionable when-to-use guidance.

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