This Claude skill provides a comprehensive PDF manipulation toolkit designed for seamless text and table extraction, document merging, and programmatic PDF creation. By leveraging industry-standard Python libraries like pypdf, pdfplumber, and reportlab, it enables automated workflows for handling complex document structures, converting PDFs into structured data, and managing large-scale file operations with high precision.

When should I use pdf?

pdf is useful in the following scenarios: • Automated Data Extraction: Extracting structured tables and text from financial statements, invoices, or research papers to populate databases or spreadsheets. • Document Assembly and Organization: Merging multiple PDF reports into a single archive or splitting large documents into individual pages for easier distribution. • Programmatic PDF Generation: Creating custom-branded PDFs, such as automated invoices, certificates, or dynamic reports using Python scripts. • High-Volume Batch Processing: Utilizing command-line tools like qpdf and poppler-utils for fast, server-side PDF optimization and text conversion.

name	pdf
description	Comprehensive PDF manipulation toolkit for extracting text and tables,
version	1.0.0

PDF Processing Guide

Quick Start

from pypdf import PdfReader, PdfWriter

# Read a PDF
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")

# Extract text
text = ""
for page in reader.pages:
    text += page.extract_text()

Python Libraries

pypdf - Basic Operations

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

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)

pdfplumber - Text and Table Extraction

Extract Tables

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)

reportlab - Create PDFs

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

c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter
c.drawString(100, height - 100, "Hello World!")
c.save()

Command-Line Tools

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

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

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

Quick Reference

Task	Best Tool	Command/Code
Merge PDFs	pypdf	`writer.add_page(page)`
Split PDFs	pypdf	One page per file
Extract text	pdfplumber	`page.extract_text()`
Extract tables	pdfplumber	`page.extract_tables()`
Create PDFs	reportlab	Canvas or Platypus
OCR scanned PDFs	pytesseract	Convert to image first

Scientific Skill Interleaving

This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:

Graph Theory

networkx [○] via bicomodule
- Universal graph hub

Bibliography References

general: 734 citations in bib.duckdb

Cat# Integration

This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:

Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826

GF(3) Naturality

The skill participates in triads satisfying:

(-1) + (0) + (+1) ≡ 0 (mod 3)

This ensures compositional coherence in the Cat# equipment structure.

pdf

When & Why to Use This Skill

Use Cases