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

The description discloses critical business logic not found in annotations, specifically the discount rule: 'they do not stack; the larger discount wins.' This is vital information for the AI to predict output or handle user expectations accurately.

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, dense sentence that front-loads the core purpose. Every word contributes to defining the tool's function and scope without unnecessary fluff.

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 the complexity of an order (7 parameters, multiple delivery options, and discount logic) and the absence of an output schema, the description is exceptionally complete in outlining the calculation parameters and inherent rules.

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?

With 71% schema coverage, the description adds significant value by elaborating on critical enum values (e.g., defining the differences between 'clear', 'frosted', and 'solid' materials). This helps the agent select the correct parameter even when given high-level user requirements.

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 defines the action (Calculates the exact total) and the resource (an order). It immediately positions the tool as the price determination method, differentiating it from order fulfillment or catalog listing siblings.

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?

While it doesn't explicitly say 'Use this before create_order', it lists the full scope of factors it calculates (material, rush, air, etc.). This comprehensive list provides clear usage boundaries and contexts for gathering user requirements before using the tool.

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