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markswendsen-code

@striderlabs/mcp-starbucks

redeem_reward

Apply a Starbucks Reward to your current cart, redeeming it when you place the order.

Instructions

Apply a Starbucks Reward to your current cart. The reward will be used when you place the order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rewardIdYesReward ID from get_rewards results
Behavior3/5

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

No annotations provided; description discloses basic behavior (applies reward, used on order) but omits side effects like reward status changes or reversibility.

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?

Single, front-loaded sentence with no wasted words; effectively communicates purpose.

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

Completeness3/5

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

For a simple tool with one parameter and no output schema, the description covers basic action but lacks details on error handling or conditions like invalid rewards.

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

Parameters3/5

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

Schema coverage is 100% (one parameter described), and the description adds no extra meaning beyond the schema's text, so baseline 3 is appropriate.

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?

The description clearly states the tool applies a Starbucks Reward to the current cart and is used when placing an order, distinguishing it from siblings like get_rewards and place_order.

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

Usage Guidelines3/5

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

The description implies usage after selecting a reward and before placing an order but lacks explicit guidance on when to use or alternatives, e.g., not using if no reward is available.

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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