genpark-coupon-recommendation-skill
GenPark coupon recommendations agent skill. Audits spend thresholds and returns the highest discount code.
Install / Use
claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-coupon-recommendation-skillIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Skill content
View source on GitHubgenpark-coupon-recommendation-skill
This repository contains the GenPark Coupon Recommendation Agent Skill — an agent configuration skill config (skill.json), a production-ready Python SDK client (coupon_recommender.py), and executable verification tests. It is designed to compare cart contents against a list of active discount vouchers, verify minimum spend thresholds and category constraints, and return the optimal coupon code.
🚀 Capabilities
- Category Restriction Audits: Limits percentage/fixed coupon values strictly to matching product categories.
- Optimal Value Solver: Compares all active discount results to select the voucher code producing the maximum savings.
- Spend Threshold Protection: Automatically flags and disqualifies coupons if cart totals fall below rules.
🛠️ Setup & Installation
- Install dependencies:
pip install -r requirements.txt
💻 SDK Usage Reference
from coupon_recommender import CouponRecommenderClient
client = CouponRecommenderClient()
result = client.recommend_coupon(
cart_items=[{"sku": "SKU-01", "price": 100, "quantity": 1, "category": "audio"}],
coupons=[
{"code": "SAVE10", "discount_type": "percent", "discount_value": 10},
{"code": "AUDIO25", "discount_type": "percent", "discount_value": 25, "applicable_category": "audio"}
]
)
print(result["recommended_coupon"])
📜 License
This project is licensed under the MIT License.
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