SEO Analytics MCP

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'extract' and 'high-impact' but doesn't clarify whether this is a read-only operation, what data source it uses (e.g., Google Search Console), potential rate limits, or what 'clusters' entail (e.g., grouping of search queries). The description is too brief to adequately inform the agent about behavioral traits.

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 a single, efficient sentence that gets straight to the point with no wasted words. It's appropriately sized for a tool with an output schema and clear naming, though its brevity contributes to gaps in other dimensions.

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 tool has 6 parameters with 0% schema coverage and no annotations, but does have an output schema, the description is incomplete. It doesn't explain parameters or behavioral context, though the output schema may cover return values. For an analytics tool with multiple parameters, more detail is needed to be fully helpful, but the presence of an output schema prevents the lowest score.

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%, so the description must compensate by explaining parameters. It adds no information about any of the 6 parameters (e.g., what 'site_url' refers to, date formats, or how 'min_query_impressions' affects results). The description fails to provide meaningful context beyond the schema's titles, leaving parameters largely 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?

The description states the tool 'extract[s] high-impact query token clusters' which indicates a verb ('extract') and resource ('clusters'), but it's vague about what 'high-impact' means and doesn't specify the data source or how it differs from sibling tools like 'analytics_query_page_opportunities' or 'gsc_top_queries'. The purpose is understandable but lacks specificity and sibling differentiation.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'to guide content focus' which implies a use case, but doesn't specify prerequisites, when to choose it over similar analytics tools, or any exclusions. This leaves the agent without clear selection criteria.

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