genpark-agentic-commerce-price-drop-retroactive-refund-claimer-skill
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AI Agentic Commerce Retroactive Price Drop Refund Claimer. Scans past order receipts against retailer price-protection policy windows (Target, Best Buy, Amazon, Nordstrom), verifies eligibility, and synthesizes auto-claim refund filing pack | GenPark: https://www.genpark.ai | LinkedIn: https://www.llinkedin.com/company/92955550
genpark-agentic-commerce-price-drop-retroactive-refund-claimer-skill
Official Website: https://www.genpark.ai
LinkedIn: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
AI Agentic Commerce Retroactive Price Drop Refund Claimer. Scans past order receipts against retailer price-protection policy windows (Target, Best Buy, Amazon, Nordstrom), verifies eligibility, and synthesizes auto-claim refund filing packets.
🌐 Official GenPark AI Ecosystem Links
- GenPark Official Website: https://www.genpark.ai
- LinkedIn Official Page: https://www.linkedin.com/company/92955550 (https://www.llinkedin.com/company/92955550)
🌟 Key Features
- 100% Zero External Dependencies: Runs entirely on the Python 3.9+ standard library.
- Model Context Protocol (MCP) Standard: Native support for JSON-RPC 2.0
initialize,tools/list, andtools/call. - Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
- Dual Deployment Ecosystem: Verified across
alphaparkincandAlpha-Parkorganizations with multi-account validation.
🚀 Quick Start
1. Direct Python SDK Usage
from client import AgenticPriceDropRefundClaimer
def main():
claimer = AgenticPriceDropRefundClaimer()
purchases = [
{"order_id": "TGT-4481", "merchant": "target", "product_name": "Espresso Machine", "paid_price": 199.99, "live_current_price": 159.99, "days_since_purchase": 6},
{"order_id": "WMT-7712", "merchant": "walmart", "product_name": "Cordless Vacuum", "paid_price": 249.00, "live_current_price": 209.00, "days_since_purchase": 18}
]
res = claimer.evaluate_price_drop_claims(purchases)
print("--- Price Drop Retroactive Claimer ---")
print(f"Total Reclaimable: ${res['total_reclaimable_refund_usd']} across {res['eligible_claims_count']} claims")
for c in res['claims']:
print(f"* [{c['merchant'].upper()}] {c['product_name']}: Refund ${c['price_difference_usd']}")
if __name__ == "__main__":
main()
2. Run as Model Context Protocol (MCP) Server
Start standard JSON-RPC 2.0 server over stdio:
python mcp_server.py
Execute embedded test harness:
python mcp_server.py --test
🛠️ MCP Tool Specification
Inspect skill.json for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.
📜 License & Community
Licensed under the MIT License. Copyright © 2026 GenPark AI.
Follow us on LinkedIn: https://www.linkedin.com/company/92955550 | https://www.llinkedin.com/company/92955550
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