sample_conversations_by_queue

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

No annotations exist beyond the title, so the description carries the behavioral burden. It discloses that the tool returns a 'representative sample' (not exhaustive), which is key. However, it omits details like required permissions, rate limits, or what happens with no matching data.

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: one for the action and one for use cases. Every word adds value, with no repetition or fluff. It is well front-loaded.

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 simplicity (3 required params, no output schema), the description is mostly complete. It explains the 'sample' behavior and general use. A minor gap: it doesn't clarify if results are paginated or the maximum sample size.

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 input schema covers 100% of parameter descriptions, so the baseline is 3. The description adds no extra meaning beyond the schema, which already explains queueId, startDate, and endDate adequately.

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 that the tool retrieves a representative sample of conversation IDs for a queue in a date range. The verb 'retrieves' and the resource 'conversation analytics' are specific, and the term 'sample' distinguishes it from sibling tools that provide full data or aggregations.

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 mentions use cases ('reporting, investigation, or summarisation') but does not specify when to avoid this tool or provide alternatives. It implies usage but lacks explicit guidance on exclusions.

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