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document-processing文件处理

Agent Skill

document-processing 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,543

周安装

182

GitHub Stars

26

下载量

1,471
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:document-processing(文件处理)
来源仓库:https://github.com/dirnbauer/webconsulting-skills
仓库路径:skills/document-processing
安装命令:
npx skills add https://github.com/dirnbauer/webconsulting-skills --skill document-processing
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dirnbauer/webconsulting-skills --skill document-processing

简介

document-processing 支持 PDF、DOCX、PPTX、XLSX 等格式创建、编辑与分析,集成多种解析工具链。

  • 适用于办公文档自动化处理、表单填写、OCR 识别或多文件合并拆分需求。
  • 根据任务类型自动选择最佳工具(如 pdfplumber、pandoc),输出结构化内容。
  • 处理敏感信息时应注意脱敏与权限控制,避免泄露原始数据或元信息。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Document Processing

Source: This skill is adapted from Anthropic's document-processing skill document processing skills (pdf, docx, pptx, xlsx) for Claude Code and AI agents.

Create, edit, and analyze office documents including PDFs, Word documents, PowerPoint presentations, and Excel spreadsheets.


Quick Reference: Which Tool to Use

TaskDocument TypeBest Tool
Extract textPDFpdfplumber, pdftotext
Merge/splitPDFpypdf, qpdf
Fill formsPDFpdf-lib (JS), pypdf
Create newPDFreportlab
OCR scannedPDFpytesseract + pdf2image
Extract textDOCXpandoc, markitdown
Create newDOCXdocx-js (JS)
Edit existingDOCXOOXML (unpack/edit/pack)
Extract textPPTXmarkitdown
Create newPPTXhtml2pptx, PptxGenJS
Edit existingPPTXOOXML (unpack/edit/pack)
Data analysisXLSXpandas
Formulas/formattingXLSXopenpyxl

PDF Processing

Text Extraction

import pdfplumber

# Extract text with layout preservation
with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        print(text)

Table Extraction

import pdfplumber
import pandas as pd

with pdfplumber.open("document.pdf") as pdf:
    all_tables = []
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            if table:
                df = pd.DataFrame(table[1:], columns=table[0])
                all_tables.append(df)

# Combine all tables
if all_tables:
    combined_df = pd.concat(all_tables, ignore_index=True)
    combined_df.to_excel("extracted_tables.xlsx", index=False)

Merge PDFs

from pypdf import PdfWriter, PdfReader

writer = PdfWriter()
for pdf_file in ["doc1.pdf", "doc2.pdf", "doc3.pdf"]:
    reader = PdfReader(pdf_file)
    for page in reader.pages:
        writer.add_page(page)

with open("merged.pdf", "wb") as output:
    writer.write(output)

Split PDF

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
    writer = PdfWriter()
    writer.add_page(page)
    with open(f"page_{i+1}.pdf", "wb") as output:
        writer.write(output)

Rotate Pages

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

page = reader.pages[0]
page.rotate(90)  # Rotate 90 degrees clockwise
writer.add_page(page)

with open("rotated.pdf", "wb") as output:
    writer.write(output)

OCR Scanned PDFs

# Requires: pip install pytesseract pdf2image
import pytesseract
from pdf2image import convert_from_path

# Convert PDF to images
images = convert_from_path('scanned.pdf')

# OCR each page
text = ""
for i, image in enumerate(images):
    text += f"Page {i+1}:\n"
    text += pytesseract.image_to_string(image)
    text += "\n\n"

print(text)

Add Watermark

from pypdf import PdfReader, PdfWriter

watermark = PdfReader("watermark.pdf").pages[0]
reader = PdfReader("document.pdf")
writer = PdfWriter()

for page in reader.pages:
    page.merge_page(watermark)
    writer.add_page(page)

with open("watermarked.pdf", "wb") as output:
    writer.write(output)

Password Protection

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

for page in reader.pages:
    writer.add_page(page)

writer.encrypt("userpassword", "ownerpassword")

with open("encrypted.pdf", "wb") as output:
    writer.write(output)

Create PDF with ReportLab

from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, PageBreak
from reportlab.lib.styles import getSampleStyleSheet

doc = SimpleDocTemplate("report.pdf", pagesize=letter)
styles = getSampleStyleSheet()
story = []

# Add content
title = Paragraph("Report Title", styles['Title'])
story.append(title)
story.append(Spacer(1, 12))

body = Paragraph("This is the body of the report. " * 20, styles['Normal'])
story.append(body)
story.append(PageBreak())

# Page 2
story.append(Paragraph("Page 2", styles['Heading1']))
story.append(Paragraph("Content for page 2", styles['Normal']))

doc.build(story)

Command Line Tools

# Extract text (poppler-utils)
pdftotext input.pdf output.txt
pdftotext -layout input.pdf output.txt  # Preserve layout

# Merge PDFs (qpdf)
qpdf --empty --pages file1.pdf file2.pdf -- merged.pdf

# Split pages
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf

# Rotate pages
qpdf input.pdf output.pdf --rotate=+90:1

# Remove password
qpdf --password=mypassword --decrypt encrypted.pdf decrypted.pdf

# Extract images
pdfimages -j input.pdf output_prefix

Word Document (DOCX) Processing

Text Extraction

# Convert to markdown with pandoc
pandoc document.docx -o output.md

# With tracked changes preserved
pandoc --track-changes=all document.docx -o output.md

Create New Document (docx-js)

import { Document, Paragraph, TextRun, HeadingLevel, Packer } from 'docx';
import * as fs from 'fs';

const doc = new Document({
  sections: [{
    properties: {},
    children: [
      new Paragraph({
        text: "Document Title",
        heading: HeadingLevel.HEADING_1,
      }),
      new Paragraph({
        children: [
          new TextRun("This is a "),
          new TextRun({
            text: "bold",
            bold: true,
          }),
          new TextRun(" word in a paragraph."),
        ],
      }),
      new Paragraph({
        text: "This is another paragraph.",
      }),
    ],
  }],
});

// Export to file
const buffer = await Packer.toBuffer(doc);
fs.writeFileSync("output.docx", buffer);

Create Document with Tables

import { Document, Paragraph, Table, TableRow, TableCell, Packer } from 'docx';

const table = new Table({
  rows: [
    new TableRow({
      children: [
        new TableCell({ children: [new Paragraph("Header 1")] }),
        new TableCell({ children: [new Paragraph("Header 2")] }),
        new TableCell({ children: [new Paragraph("Header 3")] }),
      ],
    }),
    new TableRow({
      children: [
        new TableCell({ children: [new Paragraph("Cell 1")] }),
        new TableCell({ children: [new Paragraph("Cell 2")] }),
        new TableCell({ children: [new Paragraph("Cell 3")] }),
      ],
    }),
  ],
});

const doc = new Document({
  sections: [{
    children: [
      new Paragraph({ text: "Table Example", heading: HeadingLevel.HEADING_1 }),
      table,
    ],
  }],
});

Edit Existing Document (OOXML)

For complex edits, work with raw OOXML:

  1. Unpack the document: python ooxml/scripts/unpack.py document.docx unpacked/
  2. Edit XML files (primarily word/document.xml)
  3. Validate and pack: python ooxml/scripts/validate.py unpacked/ --original document.docx python ooxml/scripts/pack.py unpacked/ output.docx

Tracked Changes Workflow

For document review with track changes:

# 1. Get current state
pandoc --track-changes=all document.docx -o current.md

# 2. Unpack
python ooxml/scripts/unpack.py document.docx unpacked/

# 3. Edit using tracked change patterns
# Use <w:ins> for insertions, <w:del> for deletions

# 4. Pack final document
python ooxml/scripts/pack.py unpacked/ reviewed.docx

PowerPoint (PPTX) Processing

Text Extraction

python -m markitdown presentation.pptx

Create New Presentation (PptxGenJS)

import PptxGenJS from 'pptxgenjs';

const pptx = new PptxGenJS();

// Slide 1 - Title
const slide1 = pptx.addSlide();
slide1.addText("Presentation Title", {
  x: 1, y: 2, w: 8, h: 1.5,
  fontSize: 36,
  bold: true,
  color: "363636",
  align: "center",
});
slide1.addText("Subtitle goes here", {
  x: 1, y: 3.5, w: 8, h: 0.5,
  fontSize: 18,
  color: "666666",
  align: "center",
});

// Slide 2 - Content
const slide2 = pptx.addSlide();
slide2.addText("Key Points", {
  x: 0.5, y: 0.5, w: 9, h: 0.8,
  fontSize: 28,
  bold: true,
});
slide2.addText([
  { text: "• First important point\n", options: { bullet: true } },
  { text: "• Second important point\n", options: { bullet: true } },
  { text: "• Third important point\n", options: { bullet: true } },
], {
  x: 0.5, y: 1.5, w: 9, h: 3,
  fontSize: 18,
});

// Slide 3 - Chart
const slide3 = pptx.addSlide();
slide3.addChart(pptx.ChartType.bar, [
  { name: "Q1", labels: ["Jan", "Feb", "Mar"], values: [100, 200, 300] },
  { name: "Q2", labels: ["Apr", "May", "Jun"], values: [150, 250, 350] },
], {
  x: 1, y: 1, w: 8, h: 4,
  showLegend: true,
  legendPos: "b",
});

// Save
pptx.writeFile("output.pptx");

Edit Existing Presentation (OOXML)

# 1. Unpack
python ooxml/scripts/unpack.py presentation.pptx unpacked/

# 2. Key files:
# - ppt/slides/slide1.xml, slide2.xml, etc.
# - ppt/notesSlides/ for speaker notes
# - ppt/theme/ for styling

# 3. Validate and pack
python ooxml/scripts/validate.py unpacked/ --original presentation.pptx
python ooxml/scripts/pack.py unpacked/ output.pptx

Create Thumbnail Grid

# Create visual overview of all slides
python scripts/thumbnail.py presentation.pptx --cols 4

Convert Slides to Images

# Convert to PDF first
soffice --headless --convert-to pdf presentation.pptx

# Then PDF to images
pdftoppm -jpeg -r 150 presentation.pdf slide
# Creates slide-1.jpg, slide-2.jpg, etc.

Excel (XLSX) Processing

Data Analysis with Pandas

import pandas as pd

# Read Excel
df = pd.read_excel('file.xlsx')  # Default: first sheet
all_sheets = pd.read_excel('file.xlsx', sheet_name=None)  # All sheets as dict

# Analyze
df.head()      # Preview data
df.info()      # Column info
df.describe()  # Statistics

# Filter and transform
filtered = df[df['Sales'] > 1000]
grouped = df.groupby('Category')['Revenue'].sum()

# Write Excel
df.to_excel('output.xlsx', index=False)

Create Excel with Formulas (openpyxl)

from openpyxl import Workbook
from openpyxl.styles import Font, PatternFill, Alignment

wb = Workbook()
sheet = wb.active

# Add data
sheet['A1'] = 'Product'
sheet['B1'] = 'Price'
sheet['C1'] = 'Quantity'
sheet['D1'] = 'Total'

# Header formatting
for cell in ['A1', 'B1', 'C1', 'D1']:
    sheet[cell].font = Font(bold=True, color='FFFFFF')
    sheet[cell].fill = PatternFill('solid', start_color='4472C4')
    sheet[cell].alignment = Alignment(horizontal='center')

# Add data rows
data = [
    ('Widget A', 10.00, 5),
    ('Widget B', 15.00, 3),
    ('Widget C', 20.00, 8),
]

for row_idx, (product, price, qty) in enumerate(data, start=2):
    sheet[f'A{row_idx}'] = product
    sheet[f'B{row_idx}'] = price
    sheet[f'C{row_idx}'] = qty
    # FORMULA - not hardcoded value!
    sheet[f'D{row_idx}'] = f'=B{row_idx}*C{row_idx}'

# Add sum formula at bottom
last_row = len(data) + 2
sheet[f'D{last_row}'] = f'=SUM(D2:D{last_row-1})'

# Column width
sheet.column_dimensions['A'].width = 15
sheet.column_dimensions['B'].width = 10
sheet.column_dimensions['C'].width = 10
sheet.column_dimensions['D'].width = 10

wb.save('output.xlsx')

Financial Model Standards

Color Coding

from openpyxl.styles import Font

# Industry-standard colors
BLUE = Font(color='0000FF')   # Hardcoded inputs
BLACK = Font(color='000000')  # Formulas
GREEN = Font(color='008000')  # Links from other sheets
RED = Font(color='FF0000')    # External links

# Apply to cells
sheet['B5'].font = BLUE   # User input
sheet['B6'].font = BLACK  # Formula

Number Formatting

# Currency with thousands separator
sheet['B5'].number_format = '$#,##0'

# Percentage with one decimal
sheet['B6'].number_format = '0.0%'

# Zeros as dashes
sheet['B7'].number_format = '$#,##0;($#,##0);"-"'

# Multiples
sheet['B8'].number_format = '0.0x'

CRITICAL: Use Formulas, Not Hardcoded Values

# ❌ WRONG - Hardcoding calculated values
total = df['Sales'].sum()
sheet['B10'] = total  # Hardcodes 5000

# ✅ CORRECT - Use Excel formulas
sheet['B10'] = '=SUM(B2:B9)'

# ❌ WRONG - Computing in Python
growth = (current - previous) / previous
sheet['C5'] = growth

# ✅ CORRECT - Excel formula
sheet['C5'] = '=(C4-C2)/C2'

Edit Existing Excel

from openpyxl import load_workbook

# Load with formulas preserved
wb = load_workbook('existing.xlsx')
sheet = wb.active

# Modify cells
sheet['A1'] = 'New Value'
sheet.insert_rows(2)
sheet.delete_cols(3)

# Add new sheet
new_sheet = wb.create_sheet('Analysis')
new_sheet['A1'] = 'Data'

wb.save('modified.xlsx')

Recalculate Formulas

After creating/modifying Excel files with formulas:

# Recalculate all formulas using LibreOffice
python recalc.py output.xlsx

Dependencies

Install as needed:

# PDF
pip install pypdf pdfplumber reportlab pytesseract pdf2image

# DOCX
npm install -g docx
pip install "markitdown[docx]"

# PPTX
npm install -g pptxgenjs
pip install "markitdown[pptx]"

# XLSX
pip install pandas openpyxl

# Command line tools
sudo apt-get install poppler-utils qpdf libreoffice pandoc

Quick Task Reference

I want to...Command/Code
Extract PDF textpdfplumber.open(f).pages[0].extract_text()
Merge PDFspypdf.PdfWriter() + loop
Split PDFOne PdfWriter() per page
OCR scanned PDFpdf2imagepytesseract
Convert DOCX to MDpandoc doc.docx -o doc.md
Create DOCXdocx-js (JavaScript)
Extract PPTX textpython -m markitdown pres.pptx
Create PPTXPptxGenJS (JavaScript)
Analyze Excelpandas.read_excel()
Excel with formulasopenpyxl

Credits & Attribution

This skill is based on the excellent work by Anthropic.

Original repository: https://github.com/anthropics/skills/tree/main/skills/document-processing

Special thanks to Anthropic for their generous open-source contributions, which helped shape this skill collection. Adapted by webconsulting.at for this skill collection

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02

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03

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.18%
按下载量换算532

Claude

30.45%
按下载量换算448

Cursor

19.46%
按下载量换算286

Gemini CLI

9.6%
按下载量换算141

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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