Route Model Selection

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

Annotations already declare readOnlyHint, destructiveHint, and idempotentHint, so the description adds value by disclosing that it uses historical performance data and cost analysis to suggest models. It is consistent with annotations and provides behavioral context beyond what annotations offer.

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, using three short sentences to convey purpose, behavioral context, and usage guidelines with no unnecessary words. It is front-loaded with the core purpose.

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 tool with three well-documented parameters and good annotations, the description is nearly complete. It explains the purpose, logic, and alternatives. However, it could briefly mention the output format (e.g., returns a model name) since no output schema is provided.

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 description coverage is 100%, so the input schema already thoroughly documents all parameters. The description does not add any additional parameter meaning beyond what the schema provides, meeting the baseline expectation.

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's purpose: 'Get a model routing recommendation for a specific task based on complexity.' It uses a specific verb and resource, and distinguishes from the sibling tool compare_models by explicitly stating what not to use it for.

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 explicit guidance on when to use the tool (for routing recommendations based on complexity) and when not to (for comparing all models). It names the alternative tool (compare_models) for static pricing, giving clear direction to the agent.

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