Seller Profit Calculator

Upload order exports from any e-commerce platform or ERP → get instant profit breakdown by order, store, SKU, and platform.

What It Does

Upload one Excel file → get a complete profit breakdown:

• 📋 Overall summary: total orders, completed, cancelled, total revenue, total cost, net profit, net margin %
• 🌍 By platform: revenue / expense / cost / profit per platform
• 🏪 By store: revenue / expense / cost / profit per store
• 🔴 Bottom 5 orders: worst loss-making orders highlighted
• 🟢 Top 5 orders: best performing orders highlighted
• ✅ Cross-check: calculated profit vs platform-declared profit — validates accuracy per order

How It Works — Agent-Powered Field Mapping

This Skill is not a static field-mapping tool. The AI Agent handles the messy reality of real export files.

The Workflow

You upload any Excel order export
        ↓
Agent reads headers + sample rows (analyze_headers.py)
        ↓
Agent identifies each column's meaning (LLM reasoning)
        ↓
Agent builds field_map JSON → passes to parse_orders.py
        ↓
parse_orders.py calculates with full field context
        ↓
Report with per-order breakdown + accuracy notes

Field Map Example

{
  "buyer_total_paid": "buyer_total_paid",
  "cost_of_goods": "cost_of_goods",
  "net_profit": "net_profit",
  "store_name": "store_name",
  "country": "country"
}

What the Agent Does

1. Auto-detects standard fields — 38 standard field names recognized across Allegro, Temu, TikTok, Amazon, etc.
2. Semantic matching for unknown columns — if a column isn't in the standard list, the Agent infers its meaning from the column name + sample values
3. Handles missing fields — if a required field is absent, the Agent notes it and estimates impact
4. Produces field_map JSON — passed directly to the parser via --field-map

CLI Usage

# Auto-detect (works if column names match standard fields)
python3 scripts/parse_orders.py orders.xlsx

# With Agent-provided field mapping
python3 scripts/parse_orders.py orders.xlsx --field-map '{"buyer_paid":"buyer_paid","item_cost":"item_cost"}'

# Or load from file
python3 scripts/parse_orders.py orders.xlsx --field-map @my_mapping.json

# Analyze file headers first (for Agent to inspect)
python3 scripts/analyze_headers.py orders.xlsx --json headers.json

Supported Platforms

All e-commerce platforms and ERPs that export order data with standard fields: order ID, revenue, costs, profit.