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

The description discloses key behavioral aspects: it returns the result, the model used, and the exact cost, and it requires an API key. These are important for the user to understand the tool's side effects and requirements. It does not mention potential errors or rate limits, but for a simple delegation tool, the provided information is adequate.

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 concise, consisting of two sentences. It front-loads the primary purpose, then states the return value and the prerequisite. There is no unnecessary verbiage, and the structure is clear and efficient.

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 that there is no output schema, the description provides a sufficient high-level summary of the return (result, model, cost) and the authentication requirement. It does not fully detail the output structure or error scenarios, but it is complete enough for an agent to understand the tool's basic behavior and decide whether to invoke it.

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?

All five parameters are fully described in the schema, so the description adds no additional nuance. The schema already covers the meaning of 'task', 'system', 'verify', 'quality', and 'max_tokens', including default values and enumerations. Therefore, the baseline score of 3 applies since schema coverage is high and the description provides no extra parameter-level detail.

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 function: handing a self-contained subtask to the cheapest capable model. It uses a specific verb ('hand') and identifies the resource (the model) and the action's purpose (offloading work to save tokens). This distinguishes it from other tools that search for models or send messages.

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: when the work doesn't require the user's own expensive model and the goal is to save tokens and move faster. It also notes the requirement of a Flow AI API key, which is a prerequisite. However, it does not explicitly name alternative tools for contrast, though the use-case condition is clear.

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