load_model

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

With no annotations, the description carries the burden of behavioral disclosure. It explains the memory target and default-promotion side effect, and warns about chat-traffic implications, but it does not mention whether triggering a load can evict other models, whether it is idempotent, or any permission/error conditions.

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, front-loaded with the core purpose, and organized with an Args section. Every sentence adds useful information without filler.

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 two-parameter tool with no output schema, the description is largely complete: parameters are precisely documented and routing/default behavior is clarified. It could go further by describing side effects on currently loaded models, but an agent can likely invoke the tool correctly with the information provided.

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?

Despite 0% schema description coverage, the description fully documents both parameters: model is tied to list_models and server-side paths, and make_default is explained with concrete guidance about default promotion and side-loaded media models. This adds significant meaning beyond the bare schema.

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 states a specific verb ('cold-load'), a specific resource (model on the remote mlx-serve server), and a specific destination (GPU memory). This clearly distinguishes it from siblings like list_models and unload_model.

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 gives useful parameter-level context, especially the warning to leave make_default false for side-loaded media models. However, it does not explicitly say when to use this tool versus alternatives like unload_model or how it relates to automatic loading behavior.

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