voicebox_llm_generate

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

No annotations provided, and description does not disclose behavioral traits such as whether generation is synchronous or async, error handling if no model is loaded, or any rate limits/auth requirements.

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?

Two short, front-loaded sentences with no wasted words. Each sentence adds distinct value: purpose and model context.

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 tool's simplicity and the presence of an output schema, the description is mostly complete. However, it could benefit from noting prerequisites (e.g., model must be loaded) or handling of null model.

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?

Schema coverage is 100%, so description adds minimal extra meaning beyond the schema. It mentions 'Qwen3 model' which slightly contextualizes the 'model' parameter but does not significantly enhance understanding.

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?

Description clearly states 'Generate text using Voicebox's built-in LLM' and specifies it uses the Qwen3 model. This distinguishes it from siblings like voicebox_generate (audio) and voicebox_speak (TTS).

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?

Implies a loaded model is needed, but does not explicitly state when to use this tool versus alternatives like voicebox_generate or voicebox_speak. No when-not or alternative tools mentioned.

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