engine_queue_depth

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

The description labels the tool as [READ] which implies non-destructive behavior, but no annotations exist. It does not disclose any behavioral traits such as performance impact, authorization needs, or output format.

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 extremely concise: a single line with a [READ] tag, a one-sentence purpose, and a bullet for the parameter. Every element is essential, and it is front-loaded.

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 low-complexity tool with no output schema, the description covers purpose and parameters adequately. However, it does not describe the return format (e.g., two numbers, dictionary) which would help an agent interpret the output.

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 explained: it accepts an inference target name or omit for default. This adds meaning beyond the schema, which has 0% description coverage. The explanation is clear and sufficient for the tool's purpose.

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 the tool reads running vs waiting requests as a backpressure signal for any engine. It distinguishes from queue_depth by specifying 'any engine', but does not explicitly differentiate from sibling tools like engine_health.

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 is provided on when to use this tool vs alternatives (e.g., queue_depth, engine_health). The description implies it's for monitoring backpressure but lacks explicit usage context or exclusions.

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