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YawLabs

@yawlabs/lemonsqueezy-mcp

by YawLabs

ls_create_checkout

Creates a checkout URL for a product variant, enabling customers to complete purchases with options for custom pricing, prefilled data, and checkout customization.

Instructions

Create a new checkout URL for a product variant. Returns a URL where the customer can complete their purchase. Supports custom pricing, prefilled customer data, and checkout customization.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeIdYesThe store ID
variantIdYesThe variant ID for the product being purchased
customPriceNoCustom price in cents (overrides the variant price)
enabledVariantsNoArray of variant IDs to show on the checkout (for products with multiple variants)
emailNoPrefill customer email
nameNoPrefill customer name
billingAddressCountryNoPrefill billing country (ISO 3166-1 alpha-2)
billingAddressZipNoPrefill billing ZIP/postal code
taxNumberNoPrefill tax/VAT number
discountCodeNoPre-apply a discount code
customDataNoCustom data object to attach to the order
expiresAtNoCheckout expiry date (ISO 8601 format)
Behavior2/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false. The description adds that it 'creates' and 'returns a URL', but does not disclose any additional behavioral traits like side effects, rate limits, or idempotency (idempotentHint=false). Minimal added value.

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 concise sentences: action, output, capabilities. No redundancy or fluff. Front-loaded with the core purpose.

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?

The description provides a good high-level overview for a tool with 12 parameters (100% schema coverage, no output schema). It could mention required fields (storeId, variantId) or constraints, but the schema covers that. Overall adequate.

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 coverage is 100% with detailed descriptions. The description summarizes key capabilities ('custom pricing, prefilled customer data, checkout customization'), mapping to parameters like customPrice, email, etc., adding context beyond the schema.

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 it creates a new checkout URL for a product variant and returns a purchase URL. It distinguishes itself from sibling tools like ls_get_checkout (reading) and ls_list_checkouts (listing).

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 for creating checkouts but lacks explicit when-to-use vs alternatives (e.g., when to use ls_create_checkout vs ls_create_customer or ls_get_checkout). No exclusion criteria provided.

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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