Pdf

This handles the full PDF workflow: reading text from existing files, creating new ones from markdown or HTML, and merging or splitting documents. It wraps PyMuPDF for most operations, with fallbacks to pdftotext and pandoc depending on what you have installed. The skill shines when you need to extract content from a PDF for analysis or programmatically generate reports. One thing to note: it assumes you're working with text-based PDFs, so if you're dealing with scanned documents, you'll need to layer in OCR separately. The markdown-to-PDF path via pandoc is surprisingly clean for generating formatted output without touching ReportLab directly.

skills.sh installs: 179
GitHub stars: 80.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add shareai-lab/learn-claude-code --skill pdf --agent claude-code

Installs into .claude/skills of the current project.

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()

SKILL.md on GitHub