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Ecommerce Data Export

作者 275254cl-hash · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
539
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版本数
在 OpenClaw 中安装
/install ecommerce-data-export
功能描述
导出电商数据为 Excel/PDF 报告,支持价格历史、销量分析、竞品对比。适合电商卖家、市场分析师。
使用说明 (SKILL.md)

电商数据导出技能

将电商数据导出为专业报告(Excel/PDF)。

功能

  1. 价格历史导出: 导出商品历史价格数据
  2. 销量分析: 生成销量趋势图表
  3. 竞品对比: 多商品对比报告
  4. 定制模板: 自定义报告格式
  5. 定时生成: 定期自动发送报告

使用方式

导出数据:

导出这个商品的价格历史为 Excel https://item.taobao.com/item.htm?id=123

生成报告:

生成我监控的 10 个商品的价格分析报告

竞品对比:

对比这 5 个商品的价格和销量,生成 PDF 报告

定时报告:

每周一早上 9 点生成上周销售报告

输出示例

生成 Excel 报告包含:

  • 商品基本信息
  • 价格历史数据表
  • 价格趋势折线图
  • 统计分析(均价、最高、最低)
  • 建议售价

变现模式

  • 免费:每月 3 次导出
  • 付费 (¥79/月):无限导出 + 定制模板
  • 付费 (¥199/月):+ 定时报告 + API 访问

优势

  • ✅ B 端刚需
  • ✅ 高客单价
  • ✅ 易传播(报告带水印)
  • ✅ 可扩展企业版

声明: 数据来自公开渠道,仅供参考。

安全使用建议
Before installing, ask the author to clarify and tighten the skill's runtime behavior: 1) Provide an explicit list of required Python packages (e.g., requests, beautifulsoup4, pdf library, scheduler) and why each is needed. 2) Explain precisely how product data is fetched (scraping vs API), whether authentication/cookies are needed, and confirm compliance with target sites' terms. 3) Describe how scheduled reports are implemented (platform scheduler vs creating cronjobs) and what persistent storage or permissions are needed. 4) Specify what credentials (SMTP, webhook, cloud storage) will be required and limit those to the minimum; avoid giving broad account keys. 5) Require explicit user confirmation before the agent sends reports or contacts external endpoints, and consider disabling autonomous invocation for scheduling actions. If the author updates the skill to explicitly list and justify dependencies and credential needs and adds safe approval points for sending data, this assessment could move toward benign; until then treat it as suspicious.
功能分析
Type: OpenClaw Skill Name: ecommerce-data-export Version: 1.0.0 The skill bundle contains only metadata and documentation (SKILL.md) for an e-commerce data export tool. It describes standard functionality for generating Excel/PDF reports using legitimate Python libraries (pandas, openpyxl) and lacks any executable code, suspicious instructions, or indicators of malicious intent.
能力评估
Purpose & Capability
The skill promises PDF generation, web scraping of product pages, and scheduled automatic sending, but declares only python3 (and a metadata note about installing pandas/openpyxl). PDF generation and web-scraping typically require additional libraries or external tools (e.g., requests/BeautifulSoup, PDF libraries, headless browser or wkhtmltopdf). The declared binaries/env vars do not justify the full feature set.
Instruction Scope
SKILL.md is vague about how data is obtained and delivered. Examples show user-provided Taobao URLs, but there are no concrete fetch/scrape instructions, nor limits on what the agent may read or send. '定时生成/定期自动发送报告' implies persistence and outbound transmission but gives no mechanism or explicit consent/checkpoints — this gives the agent broad, ill-defined discretion.
Install Mechanism
There is no formal install spec (instruction-only), but metadata suggests running 'pip3 install pandas openpyxl'. That is low-risk as-is, but is incomplete for the advertised capabilities (no scraping, networking, or PDF packages listed). No external downloads or anomalous install URLs are present.
Credentials
The skill requests no environment variables or credentials, yet describes sending reports and periodic automation — actions that normally require SMTP/API credentials, webhook URLs, or storage access. The absence of declared credential requirements is inconsistent and could lead to ad-hoc requests for secrets at runtime.
Persistence & Privilege
The skill is not set to always:true (good), but it advertises scheduled automatic reports which imply creating persistent schedules (cron jobs, background tasks, or storing credentials). SKILL.md does not state how schedules are implemented or what persistence is required; this is ambiguous and should be clarified before granting autonomous use.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install ecommerce-data-export
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ecommerce-data-export 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
ecommerce-data-export 1.0.0 初始发布 - 支持将电商数据导出为专业的 Excel 或 PDF 报告 - 提供价格历史导出、销量分析、竞品对比等多项核心功能 - 支持定制模板和定时自动生成报告 - 提供免费和付费两种使用模式,付费版支持更多高级功能 - 适合电商卖家和市场分析师,易用且可扩展
元数据
Slug ecommerce-data-export
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Ecommerce Data Export 是什么?

导出电商数据为 Excel/PDF 报告,支持价格历史、销量分析、竞品对比。适合电商卖家、市场分析师。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 539 次。

如何安装 Ecommerce Data Export?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install ecommerce-data-export」即可一键安装,无需额外配置。

Ecommerce Data Export 是免费的吗?

是的,Ecommerce Data Export 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Ecommerce Data Export 支持哪些平台?

Ecommerce Data Export 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Ecommerce Data Export?

由 275254cl-hash(@275254cl-hash)开发并维护,当前版本 v1.0.0。

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