lmstudio_health

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

With no annotations, the description carries the full burden. 'Check' implies a non-mutating probe and 'configured instances' implies multi-target scope, which is useful. However, it does not say whether the call fails when one instance is unreachable, whether it makes live network requests or reads cached state, or anything about timeouts — important for a health probe.

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?

A single front-loaded sentence with no filler. The list of inspected attributes is packed efficiently and arrives before any agent could lose interest.

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 tool with no output schema, the description adequately conveys what the agent will learn (health, latency, loaded models). It could go one step further and describe the per-instance result shape or degraded-instance behavior, but nothing essential to invoking it is missing.

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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline of 4 applies. The mention of 'configured' instances usefully signals that targeting comes from configuration rather than arguments.

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 verb (Check) and resource (configured LM Studio instances) and enumerates what is inspected: health, status, latency, and loaded models. It is distinguishable from most siblings, though the overlap with lmstudio_pool_status and lmstudio_list_models is not explicitly addressed.

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?

There is no statement of when to call this versus lmstudio_pool_status (which likely reports similar instance-level information) or lmstudio_list_models. The usage is only implied by the word 'Check' — no preconditions, no exclusions, no named alternatives.

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