ga4_gsc_page_performance

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

With no annotations provided, the description carries the full burden of behavioral transparency. It thoroughly discloses the join mechanism (normalised landing page URL), expected join rates (70-90%), potential mismatches due to URL normalisation, timezone differences, and sampling, and instructs the agent to report join rates and avoid speculation. This is exemplary transparency.

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: the first sentence states purpose, followed by two IMPORTANT sections for data caveats and analysis rules. All sentences earn their place, though the two 'IMPORTANT' blocks make it slightly verbose. Overall, it is concise and front-loaded with the core purpose.

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 of joining two data sources and the absence of an output schema, the description covers the critical caveats (join rate, timezone, sampling) and provides behavioral guidance. It does not specify the exact return format or granularity, but the purpose and constraints are sufficiently clear for an agent to invoke the tool correctly.

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?

The input schema already covers 100% of the 5 parameters with descriptions. The tool description does not add additional parameter-level semantics, so the baseline score of 3 is appropriate. No gaps in parameter understanding are introduced.

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 what the tool does: it returns landing pages with both GSC search performance metrics (clicks, impressions, position) and GA4 engagement metrics (sessions, engagement rate, conversions) side by side. This distinguishes it from sibling tools that focus on query-level or revenue data, making the purpose highly specific and actionable.

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 on when to use the tool: it requires GA4 BigQuery export and combines GSC and GA4 data for landing pages. It also gives important caveats like join rates and timezone differences, but does not explicitly name alternative tools or state when not to use this tool, so it stops short of full guidance.

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