genpark-agentic-cart-abandonment-recovery-orchestrator-skill

Autonomous Agentic Cart Abandonment Recovery Orchestrator. Monitors abandoned checkout sessions in Meta Muse, Shopify, and WhatsApp Commerce, diagnoses friction causes (shipping cost shock, size doubt, payment hesitation), crafts margin-preserving dynamic incentive vouchers, and synthesizes multi-channel win-back messages.

🌟 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 AgenticCartAbandonmentRecoveryOrchestrator."""
import sys
import json
from client import AgenticCartAbandonmentRecoveryOrchestrator

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

def main():
    print("=== Agentic Commerce Cart Abandonment Win-Back Orchestrator Demo ===")
    orchestrator = AgenticCartAbandonmentRecoveryOrchestrator()

    abandoned_session = {
        "cart_id": "CART-MUSE-89410",
        "customer_name": "Sarah Connor",
        "cart_total_usd": 150.00,
        "shipping_cost_usd": 30.00,
        "exit_step": "SHIPPING",
        "dwell_time_seconds": 75.0,
        "items": ["Smart Noise-Canceling Earbuds", "Protective Leather Case"]
    }

    # 1. Diagnose abandonment friction cause
    print("\n--- 1. Diagnosing Drop-off Friction ---")
    diagnosis = orchestrator.diagnose_abandonment_friction(abandoned_session)
    print(f"Friction Code: {diagnosis['friction_code']}")
    print(f"Recommended Strategy: {diagnosis['recommended_strategy']}")

    # 2. Synthesize profit-margin preserving win-back voucher
    print("\n--- 2. Synthesizing Dynamic Incentive Voucher ---")
    offer = orchestrator.synthesize_winback_offer(abandoned_session, profit_margin_pct=45.0)
    print(f"Voucher Code: {offer['voucher_code']} (Discount: {offer['discount_percentage']}%, Free Shipping: {offer['free_shipping_granted']})")
    print(f"Total Customer Savings: ${offer['customer_savings_usd']:.2f}")

    # 3. Generate WhatsApp and WeChat Work recovery message copy
    print("\n--- 3. Generating Channel-Native Outreach Copy ---")
    wa_msg = orchestrator.generate_recovery_message(abandoned_session, channel="WHATSAPP", offer=offer)
    print(f"[WhatsApp]:\n{wa_msg['recovery_message_text']}")

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.