local_list_models

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

With no annotations provided, the description carries the full burden. The verb 'List' clearly implies a read-only operation with no side effects, and the scope is limited to local models. It does not mention error cases or performance characteristics, but for a simple list operation this is sufficient.

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, tight sentence that conveys all necessary information without any fluff. It is front-loaded with the verb and object, making it highly readable and scannable.

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?

The description is complete for a simple, parameterless list operation. It does not specify the output format (e.g., list of names or details), but this is not essential for understanding the tool's purpose and typical usage. The local scope is clearly stated.

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 tool has no parameters, and the schema coverage is 100% (vacuously). The description adds no parameter information, but since there are none, the baseline of 3 applies. No gaps exist.

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 a specific verb ('List'), a specific resource ('models'), and a clear scope ('local Ollama instance'). It distinguishes itself from the sibling tools that perform other local operations.

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 explicit guidance is given for when to use this tool versus alternatives. However, the simplicity of the operation and lack of obvious alternatives make the usage context implicit. A more explicit mention of when to prefer this over other listing or query tools would have been clearer.

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