List downloaded LM Studio models

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

No annotations are provided, so the description carries the burden. It explicitly states 'Read-only', which is a key behavioral disclosure. It also clarifies that it lists models that are 'locally downloaded' (not necessarily loaded), adding contextual nuance. This goes beyond a bare restatement.

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, concise sentence that front-loads the action ('List'). It contains no filler, repetition, or unnecessary detail. Every word adds value.

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 tool's simplicity (no parameters) and the presence of an output schema, the description is complete. It conveys the essential purpose and the read-only nature, while the sibling tools help contextualize its niche. No additional information is needed for a user to invoke it correctly.

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 zero parameters, so there is no need for parameter explanations. Per the baseline guidance, 0 parameters warrant a score of 4. The description avoids overcomplicating things with irrelevant parameter details.

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 the specific verb 'List' and identifies the resource as 'locally downloaded models', which clearly distinguishes it from sibling tools like lmstudio_list_loaded_models. It also explicitly mentions 'discoverable metadata', defining the scope of the output.

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 clearly implies when to use this tool (when you need a list of downloaded models) but does not explicitly mention when to avoid it or use an alternative, such as lmstudio_list_loaded_models for loaded models. It lacks explicit exclusions or named alternatives.

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