kfc_delivery_estimate

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It is exceptionally transparent: it states the tool reads a checkout-time estimate, does not perform transactions, takes no payment/account info, explains the meaning of the serviceable flag, notes the effect of order_subtotal, and details defaults. This fully informs the agent of what to expect.

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 moderately lengthy but every sentence adds value. It is front-loaded with the core purpose, then explains exclusions, serviceable semantics, and parameter rationale. It is well-structured and not overly verbose given the complexity of the tool.

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 tool's complexity (12 parameters, no output schema), the description is quite complete. It covers the key output (estimated fee broken down by line item, pickup/dropoff time) and explains serviceable semantics. It doesn't fully specify the return structure, but that may be acceptable without an output schema. The description covers all major behavioral aspects.

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 baseline is 3. The description adds significant meaning beyond the schema: it explains why order_subtotal is required (affects fee), provides defaults for pickup_at and delivery_provider, and notes that store_number comes from /kfc/stores or /kfc/nearby. This extra context helps agents use parameters correctly.

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: 'Check KFC delivery serviceability and estimated fee for one store and address.' It specifies the verb (check), resource (KFC delivery serviceability and fee), and scope (one store and address). This distinguishes it from siblings like kfc_store or kfc_menu, which focus on other aspects. The statement about reading the same checkout-time estimate as KFC's site further clarifies its specific purpose.

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 explains what the tool does not do ('does not add an item to a cart or place an order, and takes no payment or account information') and clarifies when serviceable is true/false, including the reasons for false. It also explains why order_subtotal is required and mentions defaults for pickup_at and delivery_provider. However, it does not explicitly name alternative tools for when this one should not be used, though the context implies it for delivery estimation only.

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