sample_conversations_by_queue

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

Annotations only carry a title, so the description carries the full burden of behavioral disclosure. It usefully signals that results are a representative sample of IDs rather than exhaustive data, and 'Retrieves' implies a read operation. It does not mention authentication needs, rate limits, pagination, or the meaning/size of the sample.

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 two sentences with no wasted words. The action, scope, and return type are front-loaded, and the use cases are stated compactly in the second sentence.

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?

For a simple three-parameter tool with no output schema, the description covers the purpose, input scope, output type, and likely use cases. It could be more explicit about sample-size behavior or any caveats about the representative sample, but an agent has enough information to select and call the tool correctly.

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 three parameters are already documented in the input schema with types, formats, and examples, so schema coverage is 100%. The description only restates the queue-and-date-range relationship and adds no parameter-specific meaning beyond what the schema already provides.

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 names a specific action ('Retrieves'), a resource ('conversation analytics for a specific queue'), a date range, and the return type ('a representative sample of conversation IDs'). It does not explicitly contrast itself with siblings like query_queue_volumes or search_voice_conversations, but the sample-of-IDs output is a clear differentiator.

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 states useful contexts—reporting, investigation, or summarisation—which gives an agent some guidance on when to use it. However, it never mentions alternatives or says when not to use this tool, leaving the choice between this and sibling search tools mostly to inference.

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