engine_health

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

No annotations are provided, so the description must fully communicate behavioral traits. While it states the tool is a read operation, it does not explicitly confirm it is non-destructive or safe, nor does it mention any potential side effects, rate limits, or output characteristics.

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 succinct and front-loaded with the key action (READ) and purpose, followed by a single parameter explanation. Every sentence is essential, with no extraneous information.

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?

The tool has no output schema and a single optional parameter. The description lacks details about return values (e.g., a boolean or status code) and does not confirm non-destructiveness, though the simplicity of the tool reduces the need for extensive context.

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?

Schema coverage is 0%, but the description adds meaning by explaining the 'target' parameter as the inference target name from config with an option to omit for default. This provides context beyond the bare schema, partially compensating for the low coverage.

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 it is a read operation for liveness of the serving engine, specifying supported backends (vLLM, SGLang, TGI) and the tool's function via a health probe. It distinguishes itself from sibling tools like engine_queue_depth or diagnose_engine_latency.

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 provides no guidance on when to use this tool versus alternatives. It only explains the target parameter but does not mention conditions that would make this tool preferable over other health-related tools.

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