list_local_models

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

With no annotations provided, the description carries the full transparency burden. It discloses a surprising behavioral scope by noting that the tool also returns every running loopback vLLM instance, and it specifies useful output facets such as GPU fit flags, newest Hub id, and the allowlisted directory. It does not explicitly state 'read-only,' but the list-style content and zero-parameter signature make that inference strong.

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 dense but front-loaded: it opens with the catalog scope, then efficiently appends the relevant filtering and output details. There is little wasted wording, though the long colon-separated clause sequence is slightly run-on and would be clearer as a short bulleted breakdown.

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 zero-parameter listing tool, the description covers the important content areas and the surprising inclusion of running vLLM instances, so an agent has enough information to select and invoke it correctly. It does not specify the exact return structure or how the model list and instance list are combined, and there is no output schema to fill that gap.

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 and the schema already provides complete coverage, so there is no parameter-semantic burden for the description to carry. The baseline score for a no-parameter tool applies.

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 names a specific resource, the full curated catalog of local vLLM models, and explicitly contrasts it with 'a short slice,' distinguishing it from recommendation-style siblings. It also states the key discriminating contents: fit flags, Hub id resolution, allowlisted directory, and running vLLM instances. This makes the tool's purpose unmistakable.

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 phrase 'full catalog, not a short slice' implies the tool should be used when an exhaustive list is needed rather than a targeted recommendation, which gestures at alternatives like recommend_local_models. However, it never names an alternative or gives an explicit when-to-use/when-not-to-use rule, so the guidance remains implied.

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