voicebox_load_model

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

With no annotations provided, the description must disclose behavioral traits. It states the primary effect (loading into VRAM for inference) but does not mention potential side effects like memory usage, blocking behavior, or time duration. This is adequate for a simple load operation but misses transparency on performance aspects, leaving a gap.

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 extremely concise: two sentences, front-loaded with the main action, and no filler. Every word serves a purpose, making it efficient and easy to parse.

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?

The tool has one parameter and an output schema (not shown), and the description covers the core purpose and prerequisite. However, it lacks mention of any output or result indication, and given no annotations, a bit more detail (e.g., return value or confirmation of load) would enhance completeness. Still, it's largely adequate for a simple loading tool.

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 schema already covers the single parameter 'model_name' with a description and examples, achieving 100% coverage. The tool description adds no extra parameter information beyond what the schema provides, so the baseline score of 3 is appropriate.

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 ('Load a model into VRAM for inference') and the resource (model). It distinguishes from sibling tools like voicebox_download_model and voicebox_unload_model by focusing on loading into VRAM. The prerequisite is explicitly mentioned, making the purpose unambiguous.

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 provides a clear prerequisite: the model must be downloaded first, and it references voicebox_list_models for checking availability. While it doesn't explicitly state when not to use the tool or list alternatives, the context with siblings implies appropriate usage (e.g., after download, before generation). This is good guidance but lacks explicit exclusions.

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