unload_model

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

No annotations provided, so description carries full burden. It reveals that instance_id comes from load_model and may differ from model key. Provides example. Does not disclose side effects, but for a memory freeing tool it is adequate.

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 paragraphs with example code. Front-loaded with main action. Every sentence adds value. No wasted words.

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 single parameter, no annotations, and presence of output schema, description covers usage context, parameter source, and examples. Sufficient for an agent to select and invoke 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?

Only parameter instance_id has 0% schema description coverage, but description adds significant meaning: identifies the model instance, sourced from load_model, discoverable via get_loaded_models. This goes far beyond the schema's type string.

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 it unloads a model from memory to free RAM/VRAM. It specifies the resource (model instance) and action (unload). Differentiates from sibling load_model and get_loaded_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?

Description explains when to use (after loading model, to free memory) and how to discover instance IDs via get_loaded_models. Lacks explicit when-not-to-use guidance, but context is sufficient.

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