request_metrics

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

No annotations are provided, so the description bears full responsibility. It states '[READ]' implying a safe read operation, but does not disclose any behavioral traits such as side effects, required permissions, rate limits, or invocation frequency concerns. The return format is hinted but not fully specified.

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 very concise, using two sentences plus an Args section. It front-loads the key purpose and parameter info. However, the structure could be improved by listing the metrics more explicitly, but overall it is efficient.

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 one parameter and no output schema, the description adequately covers the metrics returned and the parameter. However, it lacks differentiation from similar sibling tools and does not specify the format of the target name or the exact structure of the output data. It is minimally complete but leaves gaps.

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 clear meaning to the single 'target' parameter: 'Inference target name from config; omit for the default.' This explains the parameter's purpose and default behavior beyond the basic type information in the schema.

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 reads vLLM latency metrics (TTFT, TPOT, e2e) and generation-token totals, specifying the resource and metric types. It uses a [READ] prefix indicating it is a read operation. However, it does not explicitly differentiate from the sibling tool 'engine_request_metrics' which may overlap.

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 like 'engine_request_metrics' or 'diagnose_engine_latency'. It only mentions omitting the target parameter for default behavior, but no context on appropriate use cases.

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