LM Studio status

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

Without annotations, the description carries the full burden. It does disclose 'read-only' and 'health summary', which implies safety, but it does not mention error handling (e.g., when LM Studio is not running), potential latency, or whether the counts are active/running models. Since an output schema exists, return structure is covered, but behavior beyond that is thin.

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 sentence, front-loaded with the action and clearly states the content. No wasted words.

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 params) and presence of an output schema, the description provides the essential information: it's a local, read-only health summary. However, it could mention how it differs from 'lmstudio_diagnose' to help an agent choose correctly among the many siblings.

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 is empty with 100% coverage. The description does not need to explain parameters, so baseline 4 is appropriate.

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 a specific verb ('Return') and names the resource ('local LM Studio health summary') with concrete content ('API and model counts'). It distinguishes from sibling list tools by being a summary, but does not clearly separate it from 'lmstudio_diagnose', which may also provide health-related info.

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 gives no explicit guidance on when to use this tool versus siblings like lmstudio_diagnose or lmstudio_capabilities. It only implies a read-only, quick status check but does not state alternatives or exclusions.

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