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YawLabs

@yawlabs/lemonsqueezy-mcp

by YawLabs

ls_create_discount

Create new discount codes with percentage or fixed amounts, set duration, and limit redemptions.

Instructions

Create a new discount code. Supports percentage or fixed amount discounts with optional duration and usage limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeIdYesThe store ID to create the discount in
nameYesInternal name for the discount
codeYesThe discount code customers will enter (e.g. 'SAVE20')
amountYesDiscount amount — in cents for 'fixed' type (e.g. 1000 = $10.00), or percentage for 'percent' type (e.g. 20 = 20%)
amountTypeYesDiscount type: 'percent' or 'fixed'
durationNoHow long the discount applies: 'once' (first payment only), 'repeating' (for N months), or 'forever' (default)
durationInMonthsNoNumber of months the discount applies (required when duration is 'repeating')
maxRedemptionsNoMaximum number of times this discount can be redeemed (0 = unlimited)
startsAtNoWhen the discount becomes active (ISO 8601 format)
expiresAtNoWhen the discount expires (ISO 8601 format)
isLimitedToProductsNoIf true, the discount only applies to specific variants (set via variantIds)
variantIdsNoArray of variant IDs this discount applies to (requires isLimitedToProducts: true)
Behavior3/5

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

Description matches annotations (non-readonly, non-destructive). No additional behavioral context beyond 'create' is provided, which is adequate but not enhanced.

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 sentence, no unnecessary words. Efficient and front-loaded.

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 tool with 12 parameters and no output schema, the description lacks details on return values, error conditions, or constraints (e.g., uniqueness of code). Could be more complete.

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 description coverage is 100%, so the description adds no extra value beyond the schema. Parameters are well-documented in the schema itself.

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

Purpose4/5

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

Description clearly states the action (create) and resource (discount code), and mentions supported discount types. However, it does not distinguish from sibling tools like ls_delete_discount or ls_get_discount.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives. The sibling list includes many discount-related tools, but the description does not provide context for selection.

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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