dio_predict_latency

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

With no annotations, the description carries the full burden. It frames the tool as a non-executing predictor and identifies its method and outputs, implying no request is actually sent. It stops short of stating auth requirements or response format, but nothing contradicts the non-destructive nature of the operation.

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?

Two sentences with no filler: the first states the core value proposition, the second enumerates outputs and method. Every clause earns its place and the description avoids repeating the schema.

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 simple predictor with one required string and two optional parameters, the description provides what an agent needs: what is predicted, when to call it, and the kind of result to expect. It could name the routing sibling or specify units, but those are minor gaps given the tool's low complexity and no output schema.

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 100%, so all parameters are already documented; the description adds no extra meaning about how model or tokens influence the prediction. The baseline of 3 applies because the schema carries the semantic weight.

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?

Description anchors on a concrete action ('Get') and object ('latency and cost predictions'), then lists specific outputs: queue delay, execution latency, and optimal backend. These outputs clearly distinguish it from sibling tools that list models, report cluster status, or route prompts.

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 clearly states when to use it: 'before sending requests,' establishing this as a pre-flight prediction step. It doesn't explicitly name dio_route_prompt as the alternative for actually dispatching, but the predictive-vs-executive distinction is strongly implied; no exclusions are stated.

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