Excel防错处理

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

【知行FDE】整理 CSV/Excel、制作报表并检查公式与引用;不把写入公式误报成已计算结果。

一句话选型结论

按资料字段整理

Excel防错处理是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_2b6b1a74/zhixing-excel-xlsx
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_2b6b1a74仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791621829
正文体量11.1 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
Excel防错处理当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

11.1 KB
模型实际读到的说明书原文,来自技能仓库

Excel 表格处理(改编自 Nous Research xlsx)

适合“把 CSV 整理成可筛选的表”“检查这份 Excel 的公式和异常值”“按明细生成多工作表报表”。先确认源文件、目标表、口径、输出位置;默认另存新文件,修改原件前先征求同意。对统计或财务数字先校验行列和公式范围,不凭空补值。

在 WorkBuddy 中先定位当前 SKILL.md 所在文件夹,按绝对路径调用 scripts/ 中的脚本;Windows 路径和含空格路径需加引号,命令用 python -X utf8,确保中文 JSON 可按 UTF-8 读取。需要 Python 3.10+ 与 openpyxl,缺失时提示 python -m pip install openpyxl,安装排查读 @references/setup.md。openpyxl 写入公式不等于计算出结果;只有用 Excel/LibreOffice 真正重算并读到缓存值后,才能宣称结果已核对。若没有 LibreOffice,交付文件并明确标注“公式待 Excel 打开后重算”。检查脚本 JSON 输出,尤其 recalculated 字段。插行/列前先读 @references/restructuring.md,并核对图表与条件格式等无法自动平移的部分。

以下保留原版操作细节。原版 terminal、write_file、read_file 是执行命令和读写文本的泛称,不要求 WorkBuddy 存在同名工具。来源与改动见 SOURCE_AND_CHANGES.md。

Work with Excel .xlsx workbooks using Python and openpyxl: build styled
multi-sheet workbooks with formulas and charts, inspect or dump existing
files, edit cells and structure, and convert to/from CSV. All helper
scripts are argparse CLIs that print JSON and use explicit UTF-8 I/O.

When to Use

  • Creating .xlsx reports: multiple sheets, number formats, styling,
    merged cells, freeze panes, autofilter, conditional formatting,
    charts, data-validation dropdowns, native Excel tables, defined
    names, hyperlinks, cell notes, sheet protection.
  • Reading a workbook: sheet inventory, dumping data as JSON or CSV,
    listing formulas vs cached values, notes, defined names, tables.
  • Editing existing files: set cells, append rows, insert/delete
    rows/columns (reference-aware via xlsx_restructure.py),
    copy/rename sheets, tables, names, notes, protection.
  • Recalculating formulas headlessly via LibreOffice
    (xlsx_recalc.py).
  • CSV interop with type inference and non-UTF-8 encodings.
  • Not for the legacy .xls binary format (use LibreOffice to convert
    first: soffice --headless --convert-to xlsx old.xls).

Prerequisites

  • Python 3.10+ with openpyxl (pip install openpyxl). No other
    third-party packages are needed; everything else is stdlib.
  • Optional: LibreOffice (soffice) for headless recalculation or
    format conversion.

How to Run

Resolve this skill directory first and run the helper scripts by absolute
path (every script supports --help). Quote Windows paths and spaces:

python scripts/xlsx_create.py spec.json report.xlsx   # build from JSON spec
python scripts/xlsx_read.py report.xlsx --sheets      # inventory
python scripts/xlsx_read.py report.xlsx --json --sheet Data
python scripts/xlsx_read.py report.xlsx --formulas
python scripts/xlsx_edit.py report.xlsx --sheet Data --set B2=42 --recalc
python scripts/xlsx_restructure.py report.xlsx --sheet Data --insert-rows 3:2
python scripts/xlsx_recalc.py report.xlsx
python scripts/csv_to_xlsx.py data.csv out.xlsx --encoding utf-8
python scripts/xlsx_to_csv.py report.xlsx out.csv --sheet Data

Create the UTF-8 JSON spec with the available file-writing capability;
inspect script JSON output directly or with the available file reader.

Quick Reference

Task Command
Create workbook from spec xlsx_create.py spec.json out.xlsx
Sheet names + dimensions xlsx_read.py f.xlsx --sheets
Dump sheet as JSON xlsx_read.py f.xlsx --json --sheet S
Dump sheet as CSV xlsx_read.py f.xlsx --csv --out d.csv
List formulas + cached values xlsx_read.py f.xlsx --formulas
Set a cell / formula xlsx_edit.py f.xlsx --set "A1==SUM(B:B)"
Append a row xlsx_edit.py f.xlsx --append '[1,"x",true]'
Insert 2 rows, refs NOT shifted xlsx_edit.py f.xlsx --insert-rows 3:2
Insert 2 rows, refs shifted xlsx_restructure.py f.xlsx --insert-rows 3:2
Delete a column, refs shifted xlsx_restructure.py f.xlsx --delete-cols B
Create a native table xlsx_edit.py f.xlsx --add-table Sales:A1:C9
Append inside a table --table-append 'Sales=["West",5]'
List tables xlsx_edit.py f.xlsx --list-tables
Defined names --define-name "Rates='Data'!$B$2:$B$9" / --delete-name Rates / xlsx_read.py f.xlsx --names
Hyperlink --hyperlink "A1=https://example.com|Docs"
Cell note --note "B2=Check this|Reviewer"; read via xlsx_read.py f.xlsx --notes
Protect sheet (see Pitfalls) --protect your-password --unlock B2:B9
Recalculate via LibreOffice xlsx_recalc.py f.xlsx
Copy / rename sheet --copy-sheet Src:New --rename-sheet Old:New
Force recalc on open xlsx_edit.py f.xlsx --recalc
CSV -> styled xlsx csv_to_xlsx.py in.csv out.xlsx
xlsx -> CSV xlsx_to_csv.py f.xlsx out.csv --encoding utf-8

Procedure

  1. Create: write a JSON spec (schema documented in
    xlsx_create.py --help and its docstring). Each sheet supports
    rows (scalars or styled cell objects), sparse cells overrides,
    column_widths, row_heights, merges, freeze_panes,
    autofilter, conditional_formats (cell_is rules and color
    scales), charts (bar/line/pie from cell ranges),
    validations (list dropdowns), tables (native Excel tables with
    a style name), and protection. Workbook-level defined_names
    maps names to refs. Cell objects also take hyperlink and note.
    Typed values: JSON numbers/bools
    pass through; dates use {"value": "2026-01-31", "type": "date"}.
    Number formats are Excel format strings: currency "$#,##0.00",
    percent "0.0%", date "yyyy-mm-dd".
  2. Formulas: set with "formula": "SUM(B2:B9)" in the spec or
    --set "C1==SUM(A:A)" in the editor. When writing formulas, add
    "full_calc_on_load": true (spec) or --recalc (editor); this sets
    the workbook's fullCalcOnLoad flag so Excel/LibreOffice recompute
    everything on open. openpyxl itself NEVER evaluates formulas.
  3. Read: --sheets for inventory (names, dimensions, merged
    ranges, chart count, tables, protection, defined names),
    --json/--csv for data, --formulas to
    pair each formula string with its cached result, --notes for
    cell comments, --names for defined names. Cached results
    exist only if the file was last saved by a real spreadsheet app;
    files fresh from openpyxl return null there. To materialize
    results headlessly run xlsx_recalc.py file.xlsx (uses
    LibreOffice; prints {"recalculated": false, ...} and exits 0
    when soffice is absent), then reload with --data-only.
  4. Edit: xlsx_edit.py applies renames/copies first, then
    structural row/column changes, then --set/--append. It edits in
    place unless --out is given — copy the file first if you need the
    original.
  5. Restructure: for insert/delete on sheets that have formulas,
    merges, tables, or filters, use xlsx_restructure.py instead of
    xlsx_edit.py. It rewrites formula references on ALL sheets
    (absolute $ refs, ranges, cross-sheet refs), shifts merges,
    autofilter, freeze panes, validation and conditional-format
    ranges, table refs, defined names, and row/column dimensions, then
    prints a JSON report including a not_shifted list. Rules and
    limits: references/restructuring.md.
  6. CSV interop: csv_to_xlsx.py infers int/float/bool/ISO-date
    per cell and styles the header row; xlsx_to_csv.py writes ISO
    dates and blank strings for empty cells. Both default to UTF-8 and
    accept --encoding (e.g. utf-8-sig for Excel-friendly BOM,
    cp1252 for legacy Windows exports).

Converting to PDF

LibreOffice converts headlessly (also works for CSV export of a single
sheet):

soffice --headless --convert-to pdf report.xlsx --outdir out/
soffice --headless --convert-to csv report.xlsx --outdir out/  # 1st sheet only

Only the first sheet lands in a CSV; for other sheets use
xlsx_to_csv.py --sheet NAME. If soffice is missing, install
LibreOffice or hand the file to the user unconverted.

Pitfalls

  • openpyxl does not calculate. Formula results are available only
    via load_workbook(path, data_only=True) and only when the file was
    previously saved by Excel/LibreOffice. Otherwise you get None.
  • xlsx_edit.py insert/delete does not shift references (raw
    openpyxl behavior). Use xlsx_restructure.py, which does — but even
    it cannot move chart anchors, images, or conditional-format RULE
    formulas; read its JSON report's not_shifted list and
    references/restructuring.md.
  • Sheet protection is NOT security. --protect sets the standard
    xlsx sheet-protection hash: it signals "don't edit this" to
    well-behaved apps and nothing more. Anyone can strip it by editing
    the zip's XML or unchecking it in LibreOffice. Never rely on it for
    confidentiality or integrity; it does not encrypt anything.
  • data_only=True then save silently discards all formulas
    (cached values replace them). Never save a workbook loaded that way
    unless that is the goal.
  • Loading strips charts/images: openpyxl does not round-trip
    charts, so editing a charted workbook and saving drops the charts.
    Re-add charts after editing, or avoid re-saving charted files.
  • CSV locale traps: always pass explicit encodings (the scripts
    already do) and remember European CSVs often use ; delimiters and
    decimal commas — use --delimiter ';' and expect strings like
    "12,5" to stay strings.
  • Dates are datetimes: Excel stores dates as serial numbers;
    openpyxl returns datetime/date objects. Dumps here emit ISO
    strings.
  • Sheet names are capped at 31 chars and reject [ ] : * ? / \.

Verification

  • After creating: xlsx_read.py out.xlsx --sheets and confirm sheet
    names, dimensions, merged ranges, and chart counts match intent.
  • Dump data with --json and compare against the source values.
  • After edits: re-dump the touched range; if formulas were written,
    confirm --formulas lists them and that --recalc was applied.
  • After xlsx_restructure.py: read its JSON report, then re-run
    --formulas and --sheets to confirm references and ranges landed
    where expected.
  • For a full visual check, open in LibreOffice:
    soffice --headless --convert-to pdf out.xlsx and inspect the PDF.

常见问题

5 问
答案由本站依据条目字段整理
Excel防错处理怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_2b6b1a74/zhixing-excel-xlsx。安装方式为未标注。装完刷新技能列表或重开客户端。

Excel防错处理支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

Excel防错处理权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

Excel防错处理收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

Excel防错处理用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。