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genpark-accio-shopify-operator

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: MIT
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  • Active repo — Last push 0 days ago
  • Low visibility — Only 9 GitHub stars
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SUMMARY

GenPark Distilled Skill: accio-shopify-operator

README.md

genpark-accio-shopify-operator

Tests
License
Python
Dependencies
Coverage

GenPark Accio Shopify Operator is a zero-dependency autonomous DTC e-commerce operations engine implementing logistic cart abandonment recovery modeling, stochastic inventory Reorder Point (ROP) safety stock algorithms, and multi-product tier bundling economics.

flowchart TD
    A[Abandoned Cart Parameters] --> B[Logistic Recovery Probability Model]
    B --> C[Tiered Incentive Recovery Strategy]
    D[Daily Sales & Lead Time Volatility] --> E[Stochastic ROP Equation]
    E --> F[Safety Stock Units & Reorder Point]
    G[Product Catalog & COGS] --> H[Bundle Margin & AOV Lift Optimizer]
    H --> I[High-Margin Bundle Offer]

Features

  • Cart Abandonment Predictor: Calibrated logistic model determining customer recovery likelihood and optimal intervention discounts.
  • Stochastic Inventory ROP: Formulates exact safety stock accounting for joint demand and lead-time volatility.
  • Tier Bundling Optimizer: Analyzes multi-product bundles to maximize gross profit and increase Average Order Value (AOV).

Quickstart

from client import GenParkAccioShopifyOperator

shopify = GenParkAccioShopifyOperator()
res = shopify.calculate_inventory_reorder_point_and_rop(30.0, 10.0)
print("Reorder Point Units:", res["reorder_point_units"])

License

MIT

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