voicebox_list_models

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

No annotations are provided, so the description carries full responsibility. It discloses the return structure (dict with 'models' list and fields like model_name, downloaded, etc.) and the scope (all models – TTS, STT, LLM). This is a read-only operation with no side effects, which is implicit. The description adds value beyond the empty schema, though it could explicitly state non-destructive nature.

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 concise and well-structured. The first sentence states the purpose, followed by a bullet list explaining return fields. Every sentence or line adds value, and there is no redundant information. The format is easy to scan for an AI agent.

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?

Given the context (no parameters, output schema exists, sibling tools clearly indicate this is a listing tool), the description is complete. It explains the return values, which is sufficient for a simple list operation. No additional context is needed for an agent to use it correctly.

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 input schema has zero parameters, and schema description coverage is 100%. According to guidelines, a baseline of 4 is appropriate. The description adds no parameter information (none needed) and effectively communicates what the tool does.

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 it retrieves the status of all models (TTS, Whisper, LLM). The verb 'Get' and resource 'status of all models' are specific. It distinguishes from sibling tools like voicebox_load_model, voicebox_download_model, etc., which perform different actions on individual 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 implies the tool is for checking model status but does not explicitly state when to use it over alternatives. Given the many sibling tools for model management (load, unload, download, delete), some guidance on when to list vs. use individual model actions would be beneficial. The description lacks exclusions or contextual cues.

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