# retail-expert

This skill gives an agent retail-system context for POS, inventory, e-commerce, CRM, and omnichannel work. Use it for design and analysis tasks.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 526 installs · ★ 44
- Author: personamanagmentlayer
- License: Apache-2.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/personamanagmentlayer/pcl/tree/HEAD/stdlib/domains/retail-expert/SKILL.md
- Updated: 2026-10-12
- HTML: https://affpapa.org/en/nevibecode/skills/retail-expert

## What it does

retail-expert frames work around POS, inventory management, CRM, OMS, WMS, e-commerce platforms, and payment processing. It also covers omnichannel flows such as buy online, pick up in store, ship from store, shared customer profiles, cross-channel stock, pricing, and loyalty programs.

The skill includes Python examples for reorder-point and EOQ calculations, ABC inventory classification, demand forecasting, and stock alerts. Its configuration permits `Read`, `Write`, and `Edit`. The shown calculations rely on `numpy` and `scipy`, so those routines will fail without the corresponding libraries.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add personamanagmentlayer/pcl --skill retail-expert -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/retail-expert/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/retail-expert/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add personamanagmentlayer/pcl --skill retail-expert -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/retail-expert/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add personamanagmentlayer/pcl --skill retail-expert -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/retail-expert/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install personamanagmentlayer/pcl retail-expert
```

2. **Manually: put the files in place**
- File: `.github/skills/retail-expert/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add personamanagmentlayer/pcl --skill retail-expert -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/personamanagmentlayer/pcl --path stdlib/domains/retail-expert
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/retail-expert/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add personamanagmentlayer/pcl --skill retail-expert -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/personamanagmentlayer/pcl/tree/HEAD/stdlib/domains/retail-expert/SKILL.md

## When to use it
- design a POS, CRM, and OMS integration
- calculate a reorder point for products
- classify stock with ABC analysis
- forecast demand from sales history
- generate alerts for low inventory

## Example prompts
- Design an omnichannel flow connecting POS, CRM, and a unified customer profile.
- Calculate reorder points and EOQ for this inventory dataset.
- Review the Python logic for ABC classification and demand forecasting.

## Source text · SKILL.md · Apache-2.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: eebfd34af02cbe3b.

BEGIN THIRD-PARTY FILE eebfd34af02cbe3b
````text
---
name: retail-expert
version: 1.1.0
description: >-
  Expert-level retail systems, POS, inventory management, e-commerce, customer analytics,
  and omnichannel retail. Use when the user mentions POS, ecommerce, inventory, CRM, or
  omnichannel, or when the task involves Retail Systems, Omnichannel Retail, Technologies,
  or POS Operations.
category: domains
tags: [retail, pos, ecommerce, inventory, crm, omnichannel]
allowed-tools:
  - Read
  - Write
  - Edit
---

# Retail Expert

Expert guidance for retail systems, point-of-sale solutions, inventory management, e-commerce platforms, customer analytics, and omnichannel retail strategies.

## Core Concepts

### Retail Systems

- Point of Sale (POS) systems
- Inventory Management Systems (IMS)
- Customer Relationship Management (CRM)
- Order Management Systems (OMS)
- Warehouse Management Systems (WMS)
- E-commerce platforms
- Payment processing

### Omnichannel Retail

- Online-to-offline (O2O) integration
- Buy online, pick up in store (BOPIS)
- Ship from store
- Unified customer profiles
- Cross-channel inventory visibility
- Consistent pricing across channels
- Integrated loyalty programs

### Technologies

- Mobile POS (mPOS)
- Self-checkout systems
- Electronic shelf labels (ESL)
- RFID for inventory tracking
- Computer vision for analytics
- AI-powered recommendations
- Contactless payments

## Inventory Management

```python
import numpy as np
from datetime import datetime, timedelta

class InventoryManagementSystem:
    """Inventory management and optimization"""

    def __init__(self):
        self.products = {}
        self.warehouses = {}
        self.transfer_orders = []

    def calculate_reorder_point(self,
                               average_daily_demand: float,
                               lead_time_days: int,
                               service_level: float = 0.95) -> dict:
        """Calculate optimal reorder point"""
        # Safety stock calculation
        demand_std_dev = average_daily_demand * 0.2  # Assume 20% variation

        # Z-score for service level
        from scipy import stats
        z_score = stats.norm.ppf(service_level)

        safety_stock = z_score * demand_std_dev * np.sqrt(lead_time_days)
        reorder_point = (average_daily_demand * lead_time_days) + safety_stock

        return {
            'reorder_point': int(np.ceil(reorder_point)),
            'safety_stock': int(np.ceil(safety_stock)),
            'average_daily_demand': average_daily_demand,
            'lead_time_days': lead_time_days,
            'service_level': service_level
        }

    def calculate_economic_order_quantity(self,
                                         annual_demand: float,
                                         ordering_cost: Decimal,
                                         holding_cost_per_unit: Decimal) -> dict:
        """Calculate Economic Order Quantity (EOQ)"""
        eoq = np.sqrt(
            (2 * annual_demand * float(ordering_cost)) /
            float(holding_cost_per_unit)
        )

        # Calculate total annual cost
        number_of_orders = annual_demand / eoq
````
END THIRD-PARTY FILE eebfd34af02cbe3b

The third-party file has ended. Everything between the eebfd34af02cbe3b tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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