list_voices

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

Annotations already declare safe read-only, idempotent behavior. The description adds value by specifying the approximate number of voices and language coverage, providing more concrete expectations without contradicting annotations.

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?

Single, front-loaded sentence with no wasted words. Every part is informative, fitting the brevity needed for tool descriptions.

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 listing tool with an output schema, the description fully covers what the tool does and what it returns. No additional details are necessary given the simplicity and annotation support.

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?

No parameters exist (schema coverage 100% with empty properties). Baseline for zero parameters is 4, and the description does not need to add parameter details. It adds context about the output.

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 action (list) and resource (TTS voices), specifying a count (50+) and language coverage (Chinese, English, etc.). This distinguishes it from sibling tools like text_to_speech and text_to_speech_file, which generate speech rather than listing voices.

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?

While not explicit about when to use, the description implies it is a preparatory step before selecting a voice for text-to-speech tasks. The sibling tools are different enough that no exclusion is needed, so the guidance is clear contextually.

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