engine_request_metrics

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states it is a READ operation, but lacks details on permissions, destructiveness, rate limits, or error behavior.

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 brief and front-loaded with the READ indicator and key metrics. The parameter is listed succinctly. 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 returns metrics, the description lacks details like return format, aggregation, time range, or whether metrics are per-request. With no output schema, this is insufficient for an agent to understand the response.

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 single parameter 'target' is described as 'Inference target name from config; omit for the default.' This adds context beyond the schema's type/optionality, clarifying its source and default behavior. Schema coverage is 0%, so this is valuable.

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 starts with '[READ]' and specifies the metrics: 'TTFT / TPOT / e2e latency + generation-token totals', making the purpose clear. However, it does not distinguish from sibling tools like 'request_metrics' 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?

No guidance on when to use this tool over alternatives. The description does not mention prerequisites, context, or when to avoid using it.

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