Attribution report

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

Annotations indicate readOnlyHint=true, so the description does not need to restate that. It adds parameter mapping but does not disclose other behavioral traits like data freshness, rate limits, or pagination. Given the annotations cover the safety profile, the description provides minimal additional behavioral context.

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 extremely concise: one sentence for purpose followed by parameter clarifications. It front-loads the core purpose and avoids redundancy. Every word serves a purpose, making it efficient for agent consumption.

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 (8 parameters, 4 required, output schema exists), the description is adequately complete. It covers the essential purpose and key parameter meanings. The output schema handles return values, so that omission is acceptable. However, it could provide more context on how parameters interact (e.g., model and type combinations) or typical use cases.

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 high (88%). The description adds value by clarifying the semantics of 'model' (first-click/last-click), 'type' (target dimension), and 'step' (target value) beyond the schema's enum and description fields. This helps an agent understand the parameter roles better than 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 states 'Conversion attribution', which clearly identifies the tool's function. The parameter explanations ('model is first-click or last-click; type is the target dimension; step the target value') further clarify its use. However, it does not explicitly differentiate this tool from sibling report tools like report_revenue or report_funnel, which could also involve attribution-like analyses.

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 for conversion attribution analysis but provides no explicit guidance on when to use this tool versus alternatives. No when-not-to-use or exclusion criteria are mentioned, leaving the agent to infer context from the tool name and sibling list.

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