pdf-processing

name	pdf-processing
description	Extract text, tables, and metadata from PDF files. Fill PDF forms, merge multiple PDFs, split documents, and convert PDF content to structured formats. Use when the user asks to read a PDF, extract data from a PDF, fill a form, merge PDFs, or work with PDF documents.
license	Apache-2.0
metadata	{"author":"anthropics","version":"1.0","tags":["pdf","extraction","documents","forms","ocr"],"platforms":["claude-code","cursor","any"],"triggers":["read this PDF","extract text from PDF","parse PDF","fill this PDF form","merge PDFs","split PDF","convert PDF to text","what does this PDF say","extract tables from PDF","PDF processing"]}

PDF Processing Skill

Overview

This skill handles all PDF operations: text extraction, table parsing, form filling, merging, splitting, and metadata extraction.

Step-by-Step Guidance

1. Identify the Operation

Determine what the user needs:

• Text extraction: Read content from a PDF into plain text or markdown
• Table extraction: Pull structured tabular data into CSV/JSON
• Form filling: Write values into fillable PDF form fields
• Merge: Combine multiple PDFs into one document
• Split: Divide a PDF into separate pages or sections
• Metadata: Extract author, creation date, page count, etc.

2. Choose the Right Library

For Python environments:

• pypdf (formerly PyPDF2): text extraction, merging, splitting, metadata - pure Python, no system deps
• pdfplumber: best for tables and layout-aware extraction
• pymupdf (fitz): fastest, handles scanned PDFs with OCR via Tesseract
• reportlab: generate new PDFs or fill forms programmatically
• pdfrw: low-level PDF manipulation, ideal for form filling

3. Text Extraction

import pypdf

reader = pypdf.PdfReader("document.pdf")
text = "\n\n".join(page.extract_text() for page in reader.pages)
print(text)

For layout-preserving extraction:

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        print(page.extract_text(layout=True))

4. Table Extraction

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    for page in pdf.pages:
        tables = page.extract_tables()
        for table in tables:
            for row in table:
                print(row)

5. Merging PDFs

import pypdf

merger = pypdf.PdfMerger()
for path in ["file1.pdf", "file2.pdf", "file3.pdf"]:
    merger.append(path)
merger.write("merged.pdf")
merger.close()

6. Splitting a PDF

import pypdf

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

7. Form Filling

import pypdf

reader = pypdf.PdfReader("form.pdf")
writer = pypdf.PdfWriter()
writer.append(reader)
writer.update_page_form_field_values(
    writer.pages[0],
    {"field_name": "value", "another_field": "another_value"}
)
with open("filled_form.pdf", "wb") as f:
    writer.write(f)

Edge Cases

• Scanned PDFs (image-only): use pymupdf + Tesseract OCR - warn the user if no text is found
• Password-protected PDFs: call reader.decrypt("password") before reading
• Large PDFs (>100 pages): process page by page to avoid memory issues
• Right-to-left text (Arabic, Hebrew): pdfplumber handles RTL better than pypdf

Output Format

• Plain text extraction → return as a markdown code block
• Table extraction → return as CSV or a markdown table
• File operations (merge/split) → confirm output file path and page count