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Ecommerce Full Pipeline

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anbeime
ecommerce-full-pipeline

电商运营在开展跨境电商或闲鱼捡漏业务时,若需解决选品难、上架繁琐等痛点,必用此技能!一键打通“爆品挖掘→1688采集→多平台上架→推广文案→短视频生成”全自动流水线,轻松实现端到端自动化,让开店运营效率翻倍。

Overview

Publisheranbeime
Repositoryskill
Skill nameecommerce-full-pipeline
Stars
6.9K
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645
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by anbeime on GitHub. Read the source before you install it.

Installation

Install the Ecommerce Full Pipeline AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/anbeime/skill.git /tmp/skill
mkdir -p .claude/skills
cp -r /tmp/skill/skills/ecommerce-full-pipeline/ecommerce-full-pipeline .claude/skills/ecommerce-full-pipeline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce Full Pipeline in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ecommerce Full Pipeline on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ecommerce Full Pipeline is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

跨境电商全链路自动化工具

任务目标

  • 本技能用于:跨境电商从选品到推广的全流程自动化
  • 能力包含:
    1. 1688 商品采集:关键词搜索、详情抓取、图片下载、反爬回退(Mock 数据兜底)
    2. 智能数据清洗:自动翻译标题、价格标准化、供应商评分、利润率计算、批量过滤
    3. 多平台上架:一键生成微信小店/Shopify/TikTok 上架模板,支持 CSV/Excel/JSON 导出
    4. 推广方案生成:自动关键词生成、竞品分析、广告文案撰写、预算规划
    5. 短视频创作:基于商品图片自动生成竖屏推广视频(MoviePy + Ken Burns 特效)
    6. 一键代发:1688 源头直接下单,支持无痕发货备注、Playwright 浏览器自动化
    7. 爆品趋势挖掘:多源趋势聚合(Google Trends)、6 维爆品评分、自动触发后续流水线
    8. 闲鱼选品捡漏:二手商品搜索、品牌识别、虚标过滤、6 维捡漏评分、价格监控、智能推荐
    9. 全自动流水线:爆品挖掘→采集→清洗→上架→推广→视频,一键端到端执行
  • 触发条件:用户需要开展跨境电商业务,包括选品、上架、推广、视频创作或二手选品捡漏时

前置准备

  • Python 3.8+
  • 依赖包安装:
bash
pip install requests beautifulsoup4 lxml pyyaml pytrends moviepy pillow
  • 1688 / 闲鱼需要登录态才能完整采集,建议在已登录的浏览器环境中使用
  • 推广视频生成需要 ffmpeg(MoviePy 依赖)

操作步骤

流程一:全链路自动化(推荐)

bash
# 自动挖掘爆品 → 采集 → 清洗 → 上架 → 推广 → 视频生成
python main.py auto-pipeline --seed-keywords "收纳盒,蓝牙耳机" --top-n 5 --product-limit 3 --platform all

流程二:1688 采集 → 上架 → 推广

bash
# Step 1: 采集
python main.py scrape --keyword "蓝牙耳机" --pages 2 --detail --download-images

# Step 2: 清洗(过滤毛利率低于20%、供应商评分低于60分的商品)
python main.py clean --input data/raw_products.json --min-margin 0.20 --min-score 60

# Step 3: 上架(生成多平台模板)
python main.py publish --input data/cleaned_products.json --platform all --export all

# Step 4: 推广(关键词+竞品分析+广告文案+预算)
python main.py promote --input data/cleaned_products.json --limit 10 --daily-budget 50

# Step 5: 生成推广短视频
python main.py video --input data/cleaned_products.json --limit 5 --duration 15

流程三:爆品挖掘

bash
# 自动挖掘趋势爆品
python main.py trend --categories electronics,home --top-n 10

# 指定种子词挖掘
python main.py trend --seed-keywords "充电宝,手机壳" --top-n 10

流程四:闲鱼选品捡漏

bash
# 闲鱼搜索
python main.py xianyu --keyword "投影仪" --price-max 999 --pages 3 --condition 9成新

# 捡漏搜索(带参数需求)
python main.py hunt --keyword "投影仪 4K 云台" --budget 999 \
  --min-lumens 1000 --require-4k --require-gimbal --require-wall

# 智能推荐(多关键词综合)
python main.py recommend --keywords "投影仪,家用投影,4K投影" --budget 999 \
  --min-lumens 1000 --require-4k --require-gimbal

# 价格监控
python main.py monitor --keywords "投影仪,坚果投影" --budget 999

流程五:一键代发

bash
python main.py fulfill --source-url "https://detail.1688.com/offer/xxx.html" \
  --receiver-name "张三" --receiver-phone "13800138000" \
  --receiver-address "北京市朝阳区xxx" --sku-spec "白色/大号" --quantity 1

核心逻辑

爆品挖掘评分模型

爆品评分 = 趋势速度 × 35% + (1-竞争度) × 25% + 利润潜力 × 25% + 供应稳定 × 15%

维度权重评分逻辑
趋势速度35%Google Trends 搜索量变化率,近期涨幅越高分越高
竞争度25%市场竞争强度反向指标,竞争越低分越高
利润潜力25%1688 供货价与预估售价的利润率
供应稳定15%供应商数量和供货稳定性

闲鱼捡漏评分模型

评分公式:价格优势(30分) + 性价比(20分) + 成色(15分) + 卖家信誉(15分) + 参数匹配(20分) - 风险扣分

维度分值评分逻辑
价格优势0-30实际价/合理二手价的比值越低分越高,降价幅度加分
性价比0-20相对全新价的折扣率,折扣越大分越高
成色0-15全新15分 > 几乎全新13 > 99新12 > 9成新10 > 正常使用7
卖家信誉0-15百分百好评+10,想要人数加分
参数匹配0-20按用户需求参数(亮度/4K/云台等)的匹配度
风险扣分0-30低价高参数虚标、无品牌、商家批量出货等风险因素

品牌识别与虚标过滤

  • 内置 30+ 品牌识别词典(投影仪/手机/笔记本/平板等品类)
  • 虚标检测:低价高参数异常(如 ¥200 声称 3000+ 流明)
  • 黑名单过滤:已知虚标品牌关键词、商家批量出货识别

数据清洗规则

  • 自动翻译标题为英文(上架 Shopify/TikTok)
  • 价格标准化(统一为 USD)
  • 利润率 = (预估售价 - 供货价) / 预估售价
  • 供应商评分过滤、起订量筛选

推广视频生成

  • 基于 MoviePy 自动生成竖屏短视频(9:16)
  • Ken Burns 慢推拉特效
  • 商品图片轮播 + 标题叠加
  • 时长可配置(默认 15 秒)

项目结构

ecommerce-tool/
├── main.py                  # CLI 入口(13 个子命令)
├── config.yaml              # 配置文件
├── requirements.txt         # 依赖
├── ecommerce_tool/
│   ├── scraper.py           # 1688 采集模块
│   ├── cleaner.py           # 数据清洗模块
│   ├── publisher.py          # 多平台上架模块
│   ├── promoter.py           # 推广方案模块
│   ├── video_generator.py    # 短视频生成模块
│   ├── fulfillment.py        # 一键代发模块
│   ├── trend_detector.py     # 爆品挖掘模块
│   ├── xianyu_scraper.py     # 闲鱼采集模块
│   ├── bargain_hunter.py     # 捡漏分析模块
│   └── utils.py              # 工具函数

CLI 命令一览

命令说明
scrape从 1688 采集商品
clean清洗商品数据
publish生成上架模板(微信小店/Shopify/TikTok)
promote生成推广方案(关键词/竞品/文案/预算)
video生成推广短视频
fulfill一键代发下单
pipeline全流程自动化(采集→清洗→上架→推广→视频)
trend自动挖掘爆品趋势
auto-pipeline全自动爆品流水线(挖掘→采集→上架→推广→视频)
xianyu闲鱼商品搜索
hunt闲鱼捡漏搜索
recommend智能推荐(多关键词综合)
monitor价格监控

Python API 调用

python
from ecommerce_tool.scraper import Scraper1688
from ecommerce_tool.cleaner import DataCleaner
from ecommerce_tool.publisher import Publisher
from ecommerce_tool.promoter import Promoter
from ecommerce_tool.video_generator import VideoGenerator
from ecommerce_tool.fulfillment import FulfillmentEngine
from ecommerce_tool.trend_detector import TrendDetector
from ecommerce_tool.xianyu_scraper import XianyuScraper
from ecommerce_tool.bargain_hunter import BargainHunter

# 1688 采集
scraper = Scraper1688(config, logger)
products = scraper.search("蓝牙耳机", pages=2)

# 爆品挖掘
detector = TrendDetector(config, logger)
candidates = detector.discover(categories=["electronics"], top_n=10)

# 闲鱼捡漏
hunter = BargainHunter(config, logger)
results = hunter.hunt(
    keyword="投影仪",
    price_max=999,
    spec_requirements={
        "min_lumens": 1000,
        "support_4k": True,
        "has_gimbal": True,
        "support_wall": True,
    },
)
print(hunter.display_results(results))

注意事项

  • 1688 / 闲鱼有反爬机制,建议设置合理请求间隔(1.5-3.5 秒)
  • 网络不可用时自动回退 Mock 数据(开发调试用)
  • 视频生成需要 ffmpeg 环境
  • 推广文案和关键词为 AI 生成参考,实际投放需人工审核
  • 闲鱼捡漏评分仅供选品参考,不构成交易建议
  • 虚标过滤不能 100% 消除假货,购买前请仔细核实

相关链接

Frequently asked questions

What does the Ecommerce Full Pipeline AI skill do?

电商运营在开展跨境电商或闲鱼捡漏业务时,若需解决选品难、上架繁琐等痛点,必用此技能!一键打通“爆品挖掘→1688采集→多平台上架→推广文案→短视频生成”全自动流水线,轻松实现端到端自动化,让开店运营效率翻倍。

Why use Ecommerce Full Pipeline on TypingMind?

Because you install it once and use it with any model. Ecommerce Full Pipeline is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ecommerce Full Pipeline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/anbeime/skill/tree/main/skills/ecommerce-full-pipeline/ecommerce-full-pipeline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ecommerce Full Pipeline?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ecommerce Full Pipeline?

As many as you like. As long as a model supports skills, you can use Ecommerce Full Pipeline with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ecommerce Full Pipeline AI skill free?

It is published on GitHub by anbeime. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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