Estimate AIOrouter Cost

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

Annotations already declare readOnlyHint=true, and the description adds 'Uses public retail pricing' which clarifies the data source, and the word 'Estimate' sets expectations about accuracy. This adds useful behavioral context beyond the annotation, though it doesn't mention potential error conditions or rate limits.

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 a single sentence with no fluff, front-loading the primary action and key inputs. It earns its place without unnecessary detail.

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 read-only estimation tool with three parameters and no output schema, the description adequately covers what the tool does and the pricing source. It lacks explicit return format but is sufficient for an agent to invoke correctly in most contexts.

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%, with clear descriptions for model and token parameters. The description only restates the parameter names without adding semantic detail, so the baseline score of 3 is appropriate.

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 estimates cost in USD for a prompt based on model and token counts, which is a specific action and resource. It distinguishes from sibling tools like get_pricing by framing it as a per-prompt calculation rather than a pricing catalog lookup.

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 implies usage for cost estimation but provides no explicit guidance on when to prefer this over get_pricing or other siblings. No exclusions or alternative tool mentions, so it falls to implied usage.

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