自营发货策略+分区方案配置拆分导出. 读取Excel文件，按照指定的列进行分组，将相同组的数据导出到新文件，文件命名用分组字段组合命名。

自营发货策略+分区方案配置拆分导出. 读取Excel文件，按照指定的列进行分组，将相同组的数据导出到新文件，文件命名用分组字段组合命名。

Security Scan

The skill's code and instructions match its stated purpose (splitting an Excel by group and writing new files); it does not request secrets or perform network activity, though it expects pandas to be available.

Purpose & Capability

Name/description describe grouping and exporting Excel rows; the included script implements exactly that behavior. Nothing in the files requests unrelated capabilities (no cloud, no credentials).

Instruction Scope

SKILL.md and the script keep scope to reading the provided Excel and writing grouped output files. Note: the script assumes an input column named '邮编' (postcode) in addition to the declared grouping columns; SKILL.md documents this but the code only validates the grouping columns, so missing '邮编' will raise a runtime error.

Install Mechanism

No install spec; this is an instruction-only skill with a local Python script. No network downloads or archives are performed. However, the script requires the pandas library which is not declared in metadata.

Credentials

The skill requests no environment variables, credentials, or config paths. It only reads the user-supplied Excel file and writes output files to the specified output directory.

Persistence & Privilege

always is false and the skill does not modify other skills or global agent config. It has no elevated persistence or privileged system access.

Assessment

This skill appears to do exactly what it says: split an .xlsx by specified columns and write per-group files. Before using: 1) Ensure your environment has Python and the pandas library installed (the script uses pandas but the skill metadata doesn't declare it). 2) Verify your Excel contains the grouping columns AND a '邮编' column (the script drops/uses '邮编' but only validates grouping columns). 3) Run in a directory you control (output files are written to the given --output-dir and may overwrite files with the same names). 4) For large Excel files, expect memory usage because pandas loads the sheet into memory. There is no network access or credential use in the code, so there is no hidden exfiltration in the provided files.

自营发货策略+分区方案配置拆分导出技能

快速开始

使用此技能处理Excel文件分组导出：

基本用法

1. 准备Excel文件（.xlsx格式）
2. 指定分组列（如 渠道组,实重区间,周长区间）
3. 运行分组导出脚本

脚本执行

python scripts/excel_export.py --input input.xlsx --columns "渠道组,实重区间,周长区间" --output-dir ./output/

详细说明

功能特性

• 读取Excel文件，按照指定的列进行分组，将相同组的数据导出到新文件，文件命名用分组字段组合命名. 文件名格式：{分组字段1}_{分组字段2}_{分组字段3}.xlsx
• 导出的文件需要添加 分区名称列，默认值为1
• 导出的文件需要添加 国家二字码列，默认值:US
• 导出的文件需要添加 城市列，默认值为空
• 导出的文件需要添加 开始邮编列和结束邮编列，默认值: 邮编
• 导出的文件需要删除 原所有字段仅保留新增加的 分区名称, 国家二字码, 城市, 开始邮编, 结束邮编 字段

使用示例

假设Excel文件有列：渠道组,实重区间,周长区间,邮编

• 分组列：渠道组,实重区间,周长区间
• 数据行1：渠道组=USPS, 实重区间=1, 周长区间=1, 邮编=100000 → 输出文件：USPS_1_1.xlsx
• 数据行2：渠道组=USPS, 实重区间=1, 周长区间=2, 邮编=100000 → 输出文件：USPS_1_2.xlsx
• 数据行3：渠道组=FEDEX, 实重区间=1, 周长区间=2, 邮编=100000 → 输出文件：FEDEX_1_2.xlsx

资源

• scripts/excel_export.py: 主要处理脚本