genpark-agentic-price-drop-refund-arbiter-skill

Autonomous Post-Purchase Price Drop Monitor & Retailer Refund Claim Arbiter. Tracks online purchases across Shopify, Walmart, Best Buy, and Target, detects price drops within the merchant price-match guarantee window, verifies eligibility conditions, and synthesizes automated refund claims.

🌟 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, and tools/call.
• Industrial-Grade Determinism: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
• Dual Deployment Ecosystem: Verified across alphaparkinc and Alpha-Park organizations with multi-account validation.

🚀 Quick Start

1. Direct Python SDK Usage

"""Example usage for AgenticPriceDropRefundArbiter."""
import sys
import json
from client import AgenticPriceDropRefundArbiter

sys.stdout.reconfigure(encoding='utf-8')

def main():
    print("=== Agentic Commerce Price Drop & Refund Arbiter Demo ===")
    arbiter = AgenticPriceDropRefundArbiter()

    # 1. Register post-purchase transaction
    print("\n--- 1. Registering Best Buy Purchase Receipt ---")
    receipt = arbiter.register_receipt(
        receipt_id="BB-2026-90412",
        merchant="BESTBUY",
        sku="APPLE-MBP-14",
        product_name="MacBook Pro 14-inch M4",
        purchase_price=1999.00
    )
    print(f"Registered Receipt #{receipt['receipt_id']}, Window: {receipt['window_days']} Days")

    # 2. Evaluate sudden retailer price drop
    print("\n--- 2. Evaluating Price Drop from $1999 to $1799 ---")
    evaluation = arbiter.evaluate_price_drop("BB-2026-90412", 1799.00)
    print(f"Eligible for Claim: {evaluation['eligible_for_claim']} (Savings: ${evaluation['potential_refund_usd']:.2f})")

    # 3. Synthesize autonomous refund claim letter
    print("\n--- 3. Synthesizing Retailer Price Protection Claim ---")
    claim = arbiter.synthesize_refund_claim("BB-2026-90412", 1799.00, "https://bestbuy.com/deal/APPLE-MBP-14")
    print(f"Claim ID: {claim['claim_id']}")
    print(claim["claim_letter"])

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

Licensed under the MIT License. Copyright © 2026 GenPark AI.