model_remove

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

No annotations provided, so description must fully disclose behavior. It only says 'remove from memory' and returns confirmation/error, but does not state if the model file is affected, if other references become invalid, or side effects (e.g., freeing resources). Vague.

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?

Very short and to the point without extraneous details. However, it's so concise that it sacrifices completeness. Every sentence is necessary but could be expanded.

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 simple tool with one parameter and no output schema, the description is minimally adequate but does not explain error conditions (e.g., model not found), success indication, or relationship to sibling tools like model_load. Lacks context.

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 0%, and the description only restates 'Name of the model to remove' with no added meaning beyond the schema's title. Does not clarify expected format, case sensitivity, or how to specify the model (by file path or internal name?).

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 verb 'remove' and the resource 'model from memory', distinguishing it from siblings like model_list, model_load, and model_clone, which do not remove from memory.

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?

No guidance on when to use this tool versus alternatives such as model_save before removal or model_clear. Missing prerequisites (e.g., model must be loaded) and exclusions.

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