list_voices

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

With no annotations, the description carries full behavioral disclosure. It explicitly warns that the list is static, transcribed from public docs, not fetched live, and can drift. It also clarifies the scope of the health check sibling, which is valuable beyond the function's obvious purpose.

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 compact and front-loaded with the tool's purpose, followed by essential caveats about staleness and health checking. Every clause adds value; there is no filler or redundant restatement of the tool name.

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 tool with an output schema, the description covers the essential context: what the tool lists, where the data comes from, its limitation, and how to verify current functionality via a sibling tool. Nothing important is missing.

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 already fully covers parameter semantics. The description adds useful context about what the returned voice names are and how they relate to text_to_speech, which meets the baseline for a no-parameter tool.

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 and resource: it lists known Groq PlayAI voice names for use with text_to_speech's voice argument. It clearly distinguishes this from sibling tools by tying the list directly to another tool's parameter.

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 context that this is a static list and advises that check_provider_health only verifies the default voice, not the full list. This implies when to use this tool and when to use the health-check sibling, though it does not explicitly state exclusions for speech_to_text.

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