Skill: qiji0802/seller-profit-calculator (version 1.0.2)

--- name: seller-profit-calculator description: 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. display_name: Seller Profit Calculator version: 1.0.0 author: YKGlobal tags: [ecommerce, profit-calculation, orders, temu, shein, allegro, tiktok-shop, amazon, shopee, ozon, walmart, ebay, china] --- # Seller Profit Calculator Upload order exports from **any e-commerce platform or ERP** → get instant profit breakdown by order, store, SKU, and platform. ![Profit Report](https://img.shields.io/badge/profit-report-green) ![All Platforms](https://img.shields.io/badge/-All%20Platforms-blue) ![Auto-detect](https://img.shields.io/badge/-Auto--detect-orange) ## 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 ```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 ``` --- ## 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。 --- ## Installation ```bash openclaw skill install seller-profit-calculator ``` Or use the ClawHub import URL: ``` https://clawhub.ai/import ``` --- ## 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: ``` 📊 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 ... ``` --- ## Calculation Logic ### Net Profit Formula ``` 净利润 = 平台收入 - 平台支出 - 订单成本 ``` ### Platform Income (平台收入) ``` 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) ``` 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) ``` 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。 --- ## 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). --- ## 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) | --- ## 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。 --- ## File Structure ``` 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 ``` --- ## License MIT — YKGlobal


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (MEDIUM)