pdf

jihe520's avatarfrom jihe520

Process PDF files - extract text, create PDFs, merge documents. Use when user asks to read PDF, create PDF, or work with PDF files.

⭐1stars🔀0forks📁View on GitHub🕐Updated Jan 6, 2026
[Files and Documents]

When & Why to Use This Skill

This Claude skill provides a comprehensive suite of PDF manipulation tools, enabling seamless text extraction, document creation, and file organization. It empowers users to automate complex document workflows by converting Markdown or HTML to PDF, merging multiple files, and splitting documents with high precision using industry-standard libraries like PyMuPDF and ReportLab.

Use Cases

  • Automated Data Extraction: Efficiently extract text and metadata from academic papers, financial reports, or legal documents for analysis.
  • Professional Document Generation: Convert Markdown notes or HTML templates into polished, print-ready PDF reports and manuals.
  • Document Consolidation: Merge various PDF invoices, receipts, or project assets into a single organized document for easier distribution.
  • Content Segmentation: Split large PDF books or multi-page documents into individual files for targeted processing or sharing.
  • Programmatic PDF Creation: Generate custom certificates, invoices, or data visualizations directly into PDF format using Python scripts.
namepdf
descriptionProcess PDF files - extract text, create PDFs, merge documents. Use when user asks to read PDF, create PDF, or work with PDF files.

PDF Processing Skill

You now have expertise in PDF manipulation. Follow these workflows:

Reading PDFs

Option 1: Quick text extraction (preferred)

# Using pdftotext (poppler-utils)
pdftotext input.pdf -  # Output to stdout
pdftotext input.pdf output.txt  # Output to file

# If pdftotext not available, try:
python3 -c "
import fitz  # PyMuPDF
doc = fitz.open('input.pdf')
for page in doc:
    print(page.get_text())
"

Option 2: Page-by-page with metadata

import fitz  # pip install pymupdf

doc = fitz.open("input.pdf")
print(f"Pages: {len(doc)}")
print(f"Metadata: {doc.metadata}")

for i, page in enumerate(doc):
    text = page.get_text()
    print(f"--- Page {i+1} ---")
    print(text)

Creating PDFs

Option 1: From Markdown (recommended)

# Using pandoc
pandoc input.md -o output.pdf

# With custom styling
pandoc input.md -o output.pdf --pdf-engine=xelatex -V geometry:margin=1in

Option 2: Programmatically

from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas

c = canvas.Canvas("output.pdf", pagesize=letter)
c.drawString(100, 750, "Hello, PDF!")
c.save()

Option 3: From HTML

# Using wkhtmltopdf
wkhtmltopdf input.html output.pdf

# Or with Python
python3 -c "
import pdfkit
pdfkit.from_file('input.html', 'output.pdf')
"

Merging PDFs

import fitz

result = fitz.open()
for pdf_path in ["file1.pdf", "file2.pdf", "file3.pdf"]:
    doc = fitz.open(pdf_path)
    result.insert_pdf(doc)
result.save("merged.pdf")

Splitting PDFs

import fitz

doc = fitz.open("input.pdf")
for i in range(len(doc)):
    single = fitz.open()
    single.insert_pdf(doc, from_page=i, to_page=i)
    single.save(f"page_{i+1}.pdf")

Key Libraries

Task Library Install
Read/Write/Merge PyMuPDF pip install pymupdf
Create from scratch ReportLab pip install reportlab
HTML to PDF pdfkit pip install pdfkit + wkhtmltopdf
Text extraction pdftotext brew install poppler / apt install poppler-utils

Best Practices

  1. Always check if tools are installed before using them
  2. Handle encoding issues - PDFs may contain various character encodings
  3. Large PDFs: Process page by page to avoid memory issues
  4. OCR for scanned PDFs: Use pytesseract if text extraction returns empty