gsc_ctr_benchmark

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

With no annotations, the description carries the full burden of behavioral disclosure. It provides substantial guidance: 'Base your analysis ONLY on the data returned', 'Do not speculate about causes', and detailed presentation requirements (artifacts, summary cards, colour-coded indicators). These go beyond the schema and inform the agent about analytical boundaries and output format. However, it does not disclose potential error cases or data limitations beyond the instruction to say when information is insufficient.

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 with clear sections: purpose, IMPORTANT analytical constraints, and PRESENTATION guidelines. While somewhat lengthy, each sentence contributes useful information for proper tool usage. The use of labels ('IMPORTANT', 'PRESENTATION') enhances scannability, though it could be trimmed slightly without losing value.

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?

The description covers the tool's purpose, analysis constraints, and presentation expectations, which is substantial given the absence of an output schema. It also ensures the agent knows how to handle insufficient data. However, it lacks specifics on the data returned (e.g., exact metrics or verdict thresholds), but the presentation requirements imply a rich visual output. Overall, it is complete enough for effective invocation and result interpretation.

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 100%, so the schema documents all three parameters (days, dataset, min_impressions). The tool description does not add parameter-specific information, but per the rubric, the baseline is 3 when schema coverage is high. No additional semantic value is expected, and the description does not need to compensate.

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 function: 'Compare your actual CTR per page against industry benchmarks by position' and 'Flags pages significantly underperforming for their ranking position with verdicts.' This is a specific verb+resource+scope that distinguishes it from sibling tools like gsc_ctr_opportunities or gsc_quick_wins, which likely focus on different aspects of CTR analysis.

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 implies usage context (benchmarking CTR by position) but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or alternatives. The purpose is clear enough to infer when it is appropriate, but explicit guidance is missing.

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