ga4_gsc_position_value

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

With no annotations, the description fully discloses key behaviors: URL normalization joining, join rate variability, and reasons why numbers may not match dashboards (timezone, sampling). It also instructs the agent to report exact numbers and avoid speculation, adding transparency about interpretation.

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 conveys necessary information, from the high-level question to explicit caveats. It is front-loaded with the purpose, though the repeated 'IMPORTANT' sections add length; still, no waste.

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 and lack of an output schema, the description is remarkably complete: it specifies the output (conversion rate and revenue per click by position bucket), the data prerequisites, and interpretation guidance. It also addresses potential errors in matching dashboard numbers, covering what an agent needs to know.

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 schema already describes all 4 parameters with 100% coverage, but the description adds meaningful context: the default 90 days is explained as for statistical significance, and the GA4 BigQuery export requirement ties to the dataset parameters. This elevates value beyond schema alone.

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: to show the revenue and conversion value of each ranking position. It specifies the metric (conversion rate, revenue per click) and the position buckets, distinguishing it from other GA4/GSC tools that focus on pages, queries, or content.

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 indicates prerequisites (GA4 BigQuery export) and gives context on the default 90-day window and join rate considerations. However, it does not explicitly contrast with sibling tools or state when to use it over alternatives, though the purpose itself makes the use case clear.

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