run_model_completion

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

Since annotations are absent, the description must convey behavioral traits such as output format, blocking behavior, or side effects. It only restates the core function without disclosing what the completion returns or any model-related implications. This adds minimal value beyond the tool's name.

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 redundancy. Every word contributes to the core purpose, making it highly concise. It is appropriately sized for the limited information it conveys.

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 the absence of an output schema and annotations, the description should explain return values or distinguish this tool from generate_with_tools. It does neither, leaving the tool's behavior incomplete for an agent. The simplicity of the params does not excuse the missing outcome information.

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 has 0% description coverage, and the tool description does not explain the two parameters (model_name, prompt). While the parameter names are somewhat self-explanatory, the description does not clarify their expected formats or constraints. With low schema coverage, the description fails to compensate.

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 the tool runs text generation completion on a specific local model, clearly identifying the operation and target resource. It distinguishes from sibling tools that list or stop models, though the verb 'run' is somewhat generic. Overall, the purpose is clear and specific enough.

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 is provided on when to use this tool versus alternatives like generate_with_tools or list_local_models. There is no mention of prerequisites, intended scenarios, or exclusions. The lack of any usage context leaves the agent without direction for selecting this tool.

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