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

Annotations already declare readOnlyHint, idempotentHint, closed-world, and non-destructive behavior. The description adds that rows are 'lightweight' and directs the agent to get_interview for full details, which is useful context about output scope beyond the annotations. It does not describe pagination behavior, but with page and page_size visible in the schema, the gap is minor.

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?

Two short sentences, front-loaded with the core purpose. Every phrase earns its place: the first states what the tool does, the second provides actionable context for when to use a different tool. No boilerplate or repetition.

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 output schema exists, so return values need not be explained. Annotations cover the safety profile. However, for a list tool with 7 filter parameters, the description does not explain what can be filtered or how the filters combine, leaving the agent to infer from bare schema names. It is minimally adequate but thin.

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?

There are 7 parameters with only 14% schema description coverage (only organization_id has a description). The tool description mentions no parameters at all, so it does not compensate for the low coverage. The schema provides names, types, and enums, so an agent can infer some meaning, but no added semantics (e.g., how status or quality filters behave, or how pagination works) are given.

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 uses a specific verb ('List') and resource ('interview rows'), and adds the qualifier 'lightweight' to distinguish the output from full interview details. It implicitly contrasts with get_interview by saying 'Fetch an interview to get messages, recordings, and screener responses', giving an agent enough to tell the two apart. It does not explicitly differentiate from other list_* siblings, but the resource is clear.

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 second sentence implies when to use get_interview instead of this tool: when you need messages, recordings, or screener responses. However, there is no explicit guidance on when to use list_interviews versus other list tools like list_studies or list_participants, and no exclusions or prerequisites are stated. Usage is implied rather than spelled out.

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