Seller Profit Calculator

Multi-platform Order Profit Calculator — upload order exports from any e-commerce platform or ERP, get instant profit reports by order, store, SKU, and platform.

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

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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

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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

json

{
  "交易收入": "buyer_total_paid",
  "采购金额": "cost_of_goods",
  "利润": "net_profit",
  "店铺": "store_name",
  "站点": "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

bash

# 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 '{"交易收入":"buyer_paid","采购金额":"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

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Supported Platforms

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

Platform	Export Source	Status
Allegro	ERP / Platform backend	✅ Verified
Temu 半托管	ERP / Platform backend	✅ Verified
TikTok Shop	ERP / Platform backend	✅ Verified
SHEIN	ERP / Platform backend	✅ Verified
Fruugo	ERP / Platform backend	✅ Verified
Amazon	ERP / Platform backend	✅ Compatible
Shopee / Lazada	ERP / Platform backend	✅ Compatible
Ozon	ERP / Platform backend	✅ Compatible
Walmart	ERP / Platform backend	✅ Compatible
eBay	ERP / Platform backend	✅ Compatible
其他平台	ERP / Platform backend	✅ Generic

Field mapping is automatic. 只要导出文件包含以下标准字段就能计算：订单编号、交易收入、采购成本、运费、利润。

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Installation

bash

openclaw skill install seller-profit-calculator

Or use the ClawHub import URL:

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https://clawhub.ai/import

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Usage

Quick Start

bash

# Auto-detects format — works with any platform's export
python scripts/parse_orders.py orders.xlsx

# Output JSON for further processing
python scripts/parse_orders.py orders.xlsx --json result.json

Input

Upload your order export Excel file from any platform or ERP — 妙手ERP, 千牛, 店小秘, Allegro后台, Temu后台, 亚马逊卖家中心, etc. Supported extensions: .xlsx, .xls.

Output

Markdown report printed to stdout:

text

📊 订单利润分析报告

## 📋 整体概况
| 指标 | 数值 |
|------|------|
| 总订单 | 21 |
| 平台总收入 | ¥14,145.40 |
| 平台总支出 | ¥576.66 |
| 订单总成本 | ¥12,554.53 |
| 计算净利润 | ¥1,014.21 |
| 净利率 | 7.2% |

## 🌍 按平台汇总
...

## 🔴 亏损最严重的5单
...

## 🟢 盈利最高的5单
...

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Calculation Logic

Net Profit Formula

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净利润 = 平台收入 - 平台支出 - 订单成本

Platform Income (平台收入)

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平台收入 = 交易收入 + 运费收入(绝对值) + 退款 + 其他平台补贴

Platform Expense (平台支出)

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平台支出 = 平台佣金 + 技术服务费 + 运费(平台侧)
         + 退款金额 + 违规扣款 + 关税 + VAT + 其他平台费用

Order Cost (订单成本)

text

订单成本 = 采购成本 + 头程运费 + 尾程运费 + 包材费
         + 仓库操作费 + 广告成本 + 运营成本 + 其他成本

Field mapping is automatic. 字段名自动归一化，不管导出的是"买家实付金额"还是"交易收入"还是"order_amount"，都能正确识别。

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Pricing (参考)

Tier	Price	Limits	Target
Free	¥0	10 orders/mo, 1 store	Trial
Basic	¥9.9/mo	200 orders/mo, 3 stores	Small sellers
Standard	¥29/mo	1000 orders/mo, unlimited stores	Medium sellers
Pro	¥69/mo	Unlimited orders + SKU analysis	Active sellers
Enterprise	¥149/mo	Unlimited + history + alerts	Teams

Note: This Skill itself is free to install. The tiers above apply to the hosted API version (coming soon at yk-global.com).

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Validation

Validated against real order data from multiple platforms — per-order profit match rate 100%:

Platform	Orders	Per-order Accuracy
Allegro	21	✅ Exact
Temu 半托管	28	✅ Exact (28/28)

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FAQ

Q: 我的平台不在列表里，能用吗？ A: 能用。只要导出文件包含订单号、收入、成本字段就能计算。自动识别字段映射，不限制平台。

Q: 支持 CSV 吗？ A: 目前仅支持 Excel (.xlsx / .xls)。CSV 支持在 v2.0 计划中。

Q: 利润计算为什么不等于平台后台的数字？ A: 逐单计算时，字段透明则结果精确。汇总时某些平台会有额外费用（汇率差、内部结算调整），这类费用不在导出字段中，无法通过计算还原。此时本工具的价值在于：精确定位哪一单亏、哪一单赚，为运营决策提供数据依据。

Q: 支持结算单（settlement report）吗？ A: v2.0 计划支持。目前 v1.0 读取订单维度的利润数据。

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File Structure

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seller-profit-calculator/
├── SKILL.md               ← This file
├── README.md              ← User-facing documentation
└── scripts/
    ├── parse_orders.py    ← Core parser (supports --field-map)
    └── analyze_headers.py ← Header + sample analyzer for Agent use

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License

MIT — YKGlobal