ga4_gsc_query_revenue

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the attribution method, URL normalisation join, variable join rates, timezone and sampling discrepancies, and instructs to report join rate and avoid speculation.

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 a front-loaded purpose and clear IMPORTANT markers. However, the phrase 'The revenue per keyword metric SEOs have wanted for years' adds promotional rather than operational value, keeping it from a perfect conciseness score.

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 thoroughly explains the complex join/attribution caveats and provides output-handling instructions. However, with no output schema, it does not explicitly enumerate the expected result fields (e.g., query, revenue, conversions), leaving some inference to the agent.

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?

All 5 parameters have schema descriptions (100% coverage), so the baseline is 3. The tool description does not add extra parameter-level detail beyond the schema, such as date formats or dataset naming conventions, so it meets the baseline without enhancing 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 identifies the tool as query-level revenue/conversion analysis with a specific attribution methodology (proportional click-share). It distinguishes itself from sibling tools by focusing on 'revenue per keyword' rather than page-level metrics.

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?

It gives clear context (answering which queries drive revenue), a prerequisite (GA4 BigQuery export), and handling instructions (report join rate, base analysis only on returned data). However, it does not explicitly mention alternatives or when-not-to-use cases relative to sibling tools.

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