ga4_gsc_snippet_mismatch

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

With no annotations provided, the description fully discloses important behavioral traits: URL normalization, join rate variability, timezone discrepancies (GSC Pacific vs GA4 property timezone), sampling, and instructions to report exact numbers and avoid speculation. It also tells the agent to acknowledge insufficient data rather than guess. This goes far beyond generic read-only hints and gives strong guidance on how results should be presented.

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 moderately long but each sentence earns its place, covering purpose, prerequisites, data caveats, and analyst guidelines. The use of 'IMPORTANT' emphasizes critical instructions. It could be slightly shortened by merging some caveats, but the structure is logical and not wasteful.

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's complexity (cross-platform data join, analysis constraints) and lack of output schema, the description is quite complete: it explains data limitations, instructs on reporting exact numbers, and sets boundaries for speculation. However, it does not describe the expected output format or fields, which would help the agent know what to return beyond join rate and mismatch lists. Still, this is a minor gap for such a rich description.

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 parameters with descriptions (days, max_rows, min_clicks, ga4_dataset, gsc_dataset), so the baseline is 3. The tool description does not add additional meaning to these parameters; it only indirectly references 'join rate' which is an output concept, not a parameter. Thus schema alone carries the parameter semantics.

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's purpose: 'Find pages where SERP snippet performance doesn't match on-site engagement.' It explains the two mismatch scenarios (high CTR/low engagement and low CTR/high engagement) and distinguishes this tool from sibling GSC/GA4 tools by focusing specifically on snippet-audience alignment, not just rankings or CTR.

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: it requires GA4 BigQuery export and notes that data is joined on normalized landing page URLs with typical join rates of 70-90%. It also warns about timezone and sampling differences. However, it does not explicitly mention when to use this tool over a sibling tool (e.g., ga4_gsc_page_performance) or when not to use it, so it lacks explicit alternatives.

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