List Voices

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

With no annotations provided, the description is the sole source of behavioral information. It discloses the grouping by language and the exhaustive nature ('all available'), but does not mention return format, ordering, pagination, or any prerequisites. For a simple list operation, this is adequate but not rich.

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 a single, focused sentence that is front-loaded with the essential verb and resource. It contains no wasted words and is easy to scan.

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 tool with no parameters, no annotations, and no output schema, the description covers the core purpose and a key behavioral aspect (grouping). It is sufficient for an agent to understand what the tool does and when to invoke it, though it could mention the response format for extra clarity.

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 tool has zero parameters, so the schema covers everything by default (baseline 4). The description adds value by specifying that the output is grouped by language, which enriches the meaning beyond the empty schema.

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 the tool's function: 'List all available kokoro TTS voices grouped by language.' It uses a specific verb ('list') and resource ('kokoro TTS voices'), and distinctly differentiates from sibling tools like list_models by focusing on TTS voices rather than general models.

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 provides clear context by specifying that it lists all voices grouped by language, which implies its use for discovering available voice options before text-to-speech. However, it does not explicitly mention alternatives or state when not to use this tool, leaving some room for inference.

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