List Voices

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly notes that the answer comes from a bundled catalog, incurs no API cost, and requires no arguments—this is beyond the basic purpose. It does not elaborate on return format beyond grouping, but for a simple list operation this is sufficient.

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, well-structured sentence that front-loads the purpose, then adds the behavioral/cost detail. Every clause earns its place; there is no filler or redundancy.

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 zero-parameter, read-only-like tool, the description covers all essential aspects: what the tool lists, how results are grouped, where data comes from, and that it is free of arguments and API cost. Without an output schema, the description still gives the agent enough to make a correct call.

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 zero parameters, so the schema covers everything. The description adds clarity by explicitly stating 'takes no arguments,' which prevents any guesswork about optional fields. This meets the baseline for 0-parameter tools and adds a small user-oriented confirmation.

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 states a specific verb ('List'), the precise resource ('kokoro voice ids that text_to_speech accepts'), and the grouping ('by language'). It clearly distinguishes itself from sibling tools like list_models or text_to_speech by scoping the subject to voice IDs used by text_to_speech, so an agent knows exactly what it returns.

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 gives clear usage context: it costs no API call and takes no arguments, which tells an agent when it is safe/cheap to call. However, it does not explicitly name alternatives (e.g., list_models) or state when not to use it, though the context strongly implies it is for discovering voice IDs for text_to_speech.

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