List configured discussion participants

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

No annotations exist, so description must carry behavioral disclosure. It details output fields and implies read-only operation. It could mention permissions or side effects but is adequate for a list tool.

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 sentences with no redundancy. First sentence states purpose and output; second provides usage context. Every word earns its place.

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 an output schema (existing but not shown), description does not need to detail return values. It covers the tool's purpose, output fields, and usage hint, making it complete for an agent.

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% for the single parameter, so description adds no extra meaning beyond schema. Baseline score of 3 is appropriate.

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?

Description clearly states the tool lists AI participants, specifying the fields returned (type, model, enabled/available status, default synthesizer). It distinguishes from sibling tools by noting it is useful before calling discuss, implying preparation.

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?

Description explicitly states 'Useful before calling discuss,' giving clear context for when to use. It does not exclude other use cases or compare to list_models, but the guidance is sufficient for an agent.

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