document-processing

dirnbauer/webconsulting-skills · updated Apr 8, 2026

$npx skills add https://github.com/dirnbauer/webconsulting-skills --skill document-processing
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Source: This skill is adapted from Anthropic's document-processing skill

  • document processing skills (pdf, docx, pptx, xlsx) for Claude Code and AI agents.
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

Task Document Type Best Tool
Extract text PDF pdfplumber, pdftotext
Merge/split PDF pypdf, qpdf
Fill forms PDF pdf-lib (JS), pypdf
Create new PDF reportlab
OCR scanned PDF pytesseract + pdf2image
Extract text DOCX pandoc, markitdown
Create new DOCX docx-js (JS)
Edit existing DOCX OOXML (unpack/edit/pack)
Extract text PPTX markitdown
Create new PPTX html2pptx, PptxGenJS
Edit existing PPTX OOXML (unpack/edit/pack)
Data analysis XLSX pandas
Formulas/formatting XLSX openpyxl

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 text pdfplumber.open(f).pages[0].extract_text()
Merge PDFs pypdf.PdfWriter() + loop
Split PDF One PdfWriter() per page
OCR scanned PDF pdf2imagepytesseract
Convert DOCX to MD pandoc doc.docx -o doc.md
Create DOCX docx-js (JavaScript)
Extract PPTX text python -m markitdown pres.pptx
Create PPTX PptxGenJS (JavaScript)
Analyze Excel pandas.read_excel()
Excel with formulas openpyxl

Credits & Attribution

This skill is adapted from Anthropic's Skills.

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

Copyright (c) Anthropic — The document processing skills (pdf, docx, pptx, xlsx) are source-available (not open source). See Anthropic's README for terms. Adapted by webconsulting.at for this skill collection

Thanks to Netresearch DTT GmbH for their contributions to the TYPO3 community.

Discussion

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Ratings

4.655 reviews
  • Evelyn Jain· Dec 28, 2024

    document-processing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Mateo Diallo· Dec 16, 2024

    Solid pick for teams standardizing on skills: document-processing is focused, and the summary matches what you get after install.

  • Pratham Ware· Dec 4, 2024

    Keeps context tight: document-processing is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aisha Farah· Dec 4, 2024

    I recommend document-processing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakshi Patil· Nov 23, 2024

    Registry listing for document-processing matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aisha Martin· Nov 23, 2024

    Solid pick for teams standardizing on skills: document-processing is focused, and the summary matches what you get after install.

  • Evelyn Ghosh· Nov 19, 2024

    document-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Kaira Ramirez· Nov 7, 2024

    I recommend document-processing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kiara Sethi· Oct 26, 2024

    Useful defaults in document-processing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Oct 14, 2024

    document-processing reduced setup friction for our internal harness; good balance of opinion and flexibility.

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