xlsx

GitHub

提供使用 Python (openpyxl/pandas) 读写、创建及编辑 Excel XLSX 文件的技能。涵盖数据读取分析、结构编辑、格式保留及公式处理,确保工作簿结构与样式完整,适用于电子表格相关任务。

skills/builtin/xlsx/1.0.0/SKILL.md simplexai-labs/linger

Trigger Scenarios

需要读取或分析 Excel 文件内容 需要创建新的 Excel 报表 需要编辑现有 Excel 文件并保留格式

Install

npx skills add simplexai-labs/linger --skill xlsx -g -y
More Options

Non-standard path

npx skills add https://github.com/simplexai-labs/linger/tree/main/skills/builtin/xlsx/1.0.0 -g -y

Use without installing

npx skills use simplexai-labs/linger@xlsx

指定 Agent (Claude Code)

npx skills add simplexai-labs/linger --skill xlsx -a claude-code -g -y

安装 repo 全部 skill

npx skills add simplexai-labs/linger --all -g -y

预览 repo 内 skill

npx skills add simplexai-labs/linger --list

SKILL.md

Frontmatter
{
    "name": "xlsx",
    "description": "Read, analyze, create, or edit Excel XLSX spreadsheets with Python. Use when a spreadsheet is the main input or requested output, including formulas, formatting, charts, and CSV conversion."
}

Spreadsheets with Python

Runtime

Use the current Context's isolated Python project in ./agent:

uv --directory ./agent add openpyxl
uv --directory ./agent add pandas

openpyxl handles workbook structure and presentation. Add pandas only when it helps with large table analysis or transformation; the standard library csv module is enough for simple CSV work. Run scripts with uv --directory ./agent run python ... and absolute script/input/output paths, since --directory changes the command's working directory. Save working files under ./playground/<scope>/ and publish the deliverable through the available tool.

Choose the operation

  • Read or analyze: Load the workbook with openpyxl. Inspect sheets, headers, data types, formulas, merged ranges, hidden rows or columns, and tables before interpreting values. For CSV, detect delimiter and encoding rather than assuming them.
  • Edit a workbook: Copy the source, then change only requested cells or structures. Preserve formulas, number formats, validations, named ranges, charts, and template styling where possible. When macros must survive, use load_workbook(..., keep_vba=True) and retain the .xlsm extension; check the result in a compatible application.
  • Create: Use clear column labels, appropriate number and date formats, frozen headers where useful, and native Excel formulas or charts when users need editable calculations. Do not invent input data or financial sources.
  • Analyze: Use pandas for tabular transformations if needed, then write results with openpyxl when workbook layout or formulas matter. Treat identifiers as strings when leading zeros are significant.

Example: edit while preserving workbook structure

from openpyxl import load_workbook

source = "/absolute/path/input.xlsx"
target = "/absolute/path/output.xlsx"
workbook = load_workbook(source)
sheet = workbook["Summary"]
sheet["B2"] = 42
workbook.save(target)

openpyxl stores formulas but does not calculate them. Do not present data_only=True values as freshly recalculated after an edit. If computed results are required, use an available spreadsheet calculation engine and inspect its output; the Runtime does not include LibreOffice by default. Otherwise provide formulas and state that recalculation occurs when the workbook opens in a compatible spreadsheet application.

Check the result

Reopen the saved workbook. Verify sheet names, dimensions, key values and formulas, number formats, links, charts, and any macro preservation relevant to the request. Check for broken references and formula error cells. For a styled or layout-sensitive file, inspect it in a spreadsheet renderer when one is available; report if a visual check could not be done.

Version History

  • d8ebc34 Current 2026-11-14 00:27

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Metadata

Files
0
Version
860dbfc
Hash
694007bb
Indexed
2026-11-14 00:27

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