unload_model

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states that memory is freed immediately, but does not explain whether the model remains on disk, what permissions are needed, whether the operation is reversible, or what the return behavior is.

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 a single, front-loaded sentence with no filler. It communicates the core action and immediate effect efficiently.

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 tool with no annotations, no output schema, and 0% schema description coverage, the description is too sparse. It identifies the action but omits parameter guidance, usage context, side effects, and safety information needed for reliable invocation.

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 description coverage is 0% and neither parameter has a description in the schema. The description mentions 'model' and 'ollama provider', which loosely maps to the two parameters, but it does not clarify requiredness, provider values, defaults, or what happens if provider is omitted.

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 uses a specific verb ('unload') and resource ('model'), and scopes it to VRAM on an ollama provider, which distinguishes it from disk-deletion siblings like delete_model. However, it does not explicitly name or contrast with any sibling tool, so it falls short of perfect differentiation.

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 used to free VRAM, but gives no explicit when-to-use guidance, no prerequisites, and no alternatives such as delete_model or prune_models. An agent must infer the selection context entirely.

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