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HaswanthKurevella

Coffee Shop MCP

place_order

Place a coffee order after the customer selects a drink and customizations. Returns an order ID and the machine steps to prepare the drink.

Instructions

Place a coffee order. Call this once the customer has chosen a drink and confirmed their customizations. Returns an order ID and the recipe (the ordered list of machine steps to make the drink). drink must be on the menu; size is small/medium/large; extra_shot adds a second shot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNomedium
drinkYes
extra_shotNo
Behavior4/5

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

Without annotations, description carries full burden. It details return values (order ID and recipe), constraints (drink on menu, size options), and extra_shot behavior. Lacks side effects like cost or inventory, but good overall.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences: purpose+timing, return values, parameter details. No wasted words, front-loaded with key info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers purpose, when to use, parameters, return values. Lacks error handling or success criteria, but for a simple order tool with 3 params and no output schema, it's fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, so description compensates. It explains drink must be on menu, size is small/medium/large, extra_shot adds a second shot. Could be more precise about size values, but adds significant meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Place a coffee order' with specific verb and resource. It distinguishes from sibling tools like check_order_status and get_menu by focusing on order placement after customer confirms customizations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Call this once the customer has chosen a drink and confirmed their customizations', providing clear context. Doesn't explicitly state when not to use, but alternatives are implied by sibling tool names.

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

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