SEO Analytics MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool runs a report but doesn't clarify if it's read-only, requires authentication, has rate limits, returns paginated data, or handles errors. The mention of 'optional dimension/metric filters and ordering' hints at customization but lacks operational details needed for safe invocation.

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 front-loads the core action ('Run raw GA4 report') and adds key modifiers ('with optional dimension/metric filters and ordering'). There's no wasted verbiage, making it easy to parse quickly.

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 (12 parameters, no annotations, 0% schema coverage) and the presence of an output schema (which reduces need to describe return values), the description is incomplete. It covers the basic purpose but lacks usage guidelines, parameter explanations, and behavioral context. For a tool with many parameters and no annotations, more detail is needed to be fully helpful.

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?

With 12 parameters and 0% schema description coverage, the schema provides only titles (e.g., 'Property Id', 'Start Date') without explanations. The description mentions 'optional dimension/metric filters and ordering', which loosely relates to parameters like 'dimensions', 'metrics', 'dimension_filter', 'metric_filter', and 'order_bys', but doesn't explain their formats, required values, or interactions. It fails to compensate for the schema's lack of detail.

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 action ('Run') and resource ('raw GA4 report'), specifying it's for GA4 (Google Analytics 4) reports. It mentions optional dimension/metric filters and ordering, which adds specificity. However, it doesn't distinguish this tool from sibling tools like 'ga4_channel_report' or 'analytics_trend_report', which likely serve different analytical purposes.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a GA4 property), exclusions, or compare it to sibling tools like 'ga4_channel_report' (which might be for specific channel analysis) or 'analytics_trend_report' (which might focus on trends). This leaves the agent without context for tool selection.

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