Benchmark local LM Studio

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

With no annotations provided, the description carries the full burden of disclosure. It does communicate important behavioral constraints: 'at most five' limits the number of requests, 'small' suggests resource usage limits, and 'report only measurements actually available' indicates no fabricated data. However, it does not disclose potential side effects, whether the tool modifies system state, or what happens when the LM Studio server is unavailable. This is a basic level of transparency but not comprehensive.

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, well-structured sentence that front-loads the core action and constraints. Every word contributes: 'at most five' specifies the limit, 'small' hints at request size, 'streaming requests' describes the method, and 'report only measurements actually available' clarifies output principles. There is zero wasted verbiage, making it appropriately concise.

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 has 3 parameters, no annotations, and no output schema, the description is not complete enough. It lacks details on what specific measurements are reported, how output is presented, error handling, and when to choose this over the many test and diagnostic sibling tools. The description provides a high-level overview but misses critical context needed for reliable invocation and interpretation.

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 input schema has 0% description coverage, so the description must compensate for parameter meaning. The description only implies that requests are 'small' and limited to 'at most five', which loosely relates to the `runs` parameter, but it does not explain the `model` or `prompt` parameters, nor does it clarify the relationship between `runs` and the actual number of requests. The agent receives no help in understanding how to correctly set these parameters beyond their names and types.

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 action: 'Run at most five small streaming requests and report only measurements actually available.' It identifies the tool as a benchmark for local LM Studio with a defined scope. However, it doesn't explicitly distinguish it from similar sibling tools like lmstudio_test_inference or lmstudio_test_streaming_tool_calling, relying on the word 'benchmark' to convey its measurement focus.

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 on when to use this tool versus alternatives is provided. The description does not mention any prerequisites, exclusions, or situations where another sibling tool would be more appropriate. The implied context is 'to benchmark', but the lack of explicit alternative guidance leaves the agent to infer usage.

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