op3_audience_summary

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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds valuable interpretation of the key metric, downloadsPerListener, and warns that other download figures are inflated by re-requests. This goes beyond the annotations and helps the agent understand the result's meaning.

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 compact and front-loaded with the core purpose. The second sentence explains interpretation of the key metric without unnecessary filler. Every part adds 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?

With no output schema, the description helpfully explains the central output concept, downloadsPerListener. Parameter semantics are fully covered by the schema, and annotations cover safety. It could be more explicit about the full set of returned fields, but it is sufficient for an agent to select and invoke the tool effectively.

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 fully documents all four parameters. The description adds only general context like 'over any window' but does not provide additional parameter-level detail beyond what the schema already includes, meriting the baseline score.

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 a specific, meaningful objective: compute unique listeners against downloads for a show over any window. It clearly differentiates from other endpoints by emphasizing 'how many people, not how many requests,' which distinguishes it from download-focused sibling tools.

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 implicitly tells the agent when to use this tool: when the true audience size matters and when other endpoints only provide request counts. It says 'every rolled-up endpoint cannot give you' this number, giving clear usage context, though it does not explicitly name alternative tools or exclusion criteria.

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