Pdf

PDF Processing Guide

🎯 Load Full PAI Context

Before starting any task with this skill, load complete PAI context:

read ${PAI_HOME}/SKILL.md

This provides access to:

• Complete contact list (Angela, Bunny, Saša, Greg, team members)
• Stack preferences (TypeScript>Python, bun>npm, uv>pip)
• Security rules and repository safety protocols
• Response format requirements (structured emoji format)
• Voice IDs for agent routing (ElevenLabs)
• Personal preferences and operating instructions

When to Activate This Skill

Direct PDF Task Triggers

• User wants to create a new PDF document
• User wants to merge, combine, or concatenate multiple PDFs
• User wants to split or separate a PDF into individual pages/sections
• User mentions "extract text from PDF", "PDF text extraction"
• User mentions "extract tables from PDF", "PDF tables"
• User wants to "fill PDF form", "PDF form filling"
• User mentions "OCR", "scanned PDF", or "scan to text"
• User wants to add watermarks, password protection, or encryption
• User wants to extract images from a PDF
• User wants to rotate pages or manipulate PDF structure

Contextual Triggers

• User provides a .pdf file path for processing
• User mentions form filling automation or batch PDF processing
• User needs to process PDFs programmatically at scale

🔀 PDF Workflow Routing

This skill supports multiple PDF processing workflows:

Creation Workflow

Trigger: "create PDF", "generate PDF", "make PDF", "PDF from data"

Tools: reportlab (Python) Documentation: Lines 136-181 (SKILL.md)

Use Cases:

• Creating new PDFs from scratch
• Generating reports programmatically
• Multi-page documents with text and graphics
• PDF generation from templates or data

Merge/Split Workflow

Trigger: "merge PDFs", "combine PDFs", "split PDF", "separate pages"

Tools: pypdf (Python), qpdf (CLI) Documentation: Lines 46-68 (SKILL.md), Lines 199-211 (qpdf)

Use Cases:

• Combining multiple PDFs into one document
• Splitting PDFs into individual pages or ranges
• Reorganizing PDF page order
• Extracting specific page ranges

Text Extraction Workflow

Trigger: "extract text", "PDF to text", "read PDF content"

Tools: pdfplumber (Python), pdftotext (CLI) Documentation: Lines 95-103 (pdfplumber), Lines 186-196 (pdftotext)

Use Cases:

• Extracting text while preserving layout
• Converting PDFs to plain text
• Batch text extraction from multiple PDFs
• Metadata extraction

Table Extraction Workflow

Trigger: "extract tables", "PDF tables", "table data from PDF"

Tools: pdfplumber + pandas (Python) Documentation: Lines 106-133 (SKILL.md)

Use Cases:

• Extracting structured table data to Excel/CSV
• Financial data extraction from PDF reports
• Converting PDF tables to dataframes
• Multi-table extraction and combination

Form Filling Workflow

Trigger: "fill PDF form", "PDF form filling", "complete PDF form"

Tools: pdf-lib (JavaScript) or pypdf (Python) Documentation: forms.md (complete guide)

Use Cases:

• Programmatic form completion
• Batch form processing
• Template-based PDF generation
• Form field population from data sources

OCR Workflow

Trigger: "OCR", "scanned PDF", "extract text from scan", "image to text"

Tools: pytesseract + pdf2image (Python) Documentation: Lines 227-244 (SKILL.md)

Use Cases:

• Extracting text from scanned documents
• Processing image-based PDFs
• Converting scanned forms to editable text
• Legacy document digitization

Manipulation Workflow

Trigger: "watermark", "password protect", "encrypt PDF", "rotate pages", "extract images"

Tools: pypdf (Python), pdfimages (CLI) Documentation: Lines 246-288 (SKILL.md)

Use Cases:

• Adding watermarks to PDFs
• Password protection and encryption
• Page rotation and transformation
• Image extraction from PDFs

Overview

This guide covers essential PDF processing operations using Python libraries and command-line tools. For advanced features, JavaScript libraries, and detailed examples, see reference.md. If you need to fill out a PDF form, read forms.md and follow its instructions.

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)

Extract Metadata

reader = PdfReader("document.pdf")
meta = reader.metadata
print(f"Title: {meta.title}")
print(f"Author: {meta.author}")
print(f"Subject: {meta.subject}")
print(f"Creator: {meta.creator}")

Rotate Pages

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)

pdfplumber - Text and Table Extraction

Extract Text with Layout

import pdfplumber

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

Extract Tables

with pdfplumber.open("document.pdf") as pdf:
    for i, page in enumerate(pdf.pages):
        tables = page.extract_tables()
        for j, table in enumerate(tables):
            print(f"Table {j+1} on page {i+1}:")
            for row in table:
                print(row)

Advanced Table Extraction

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:  # Check if table is not empty
                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)

reportlab - Create PDFs

Basic PDF Creation

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

c = canvas.Canvas("hello.pdf", pagesize=letter)
width, height = letter

# Add text
c.drawString(100, height - 100, "Hello World!")
c.drawString(100, height - 120, "This is a PDF created with reportlab")

# Add a line
c.line(100, height - 140, 400, height - 140)

# Save
c.save()

Create PDF with Multiple Pages

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']))

# Build PDF
doc.build(story)

Command-Line Tools

pdftotext (poppler-utils)

# Extract text
pdftotext input.pdf output.txt

# Extract text preserving layout
pdftotext -layout input.pdf output.txt

# Extract specific pages
pdftotext -f 1 -l 5 input.pdf output.txt  # Pages 1-5

qpdf

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

# Split pages
qpdf input.pdf --pages . 1-5 -- pages1-5.pdf
qpdf input.pdf --pages . 6-10 -- pages6-10.pdf

# Rotate pages
qpdf input.pdf output.pdf --rotate=+90:1  # Rotate page 1 by 90 degrees

# Remove password
qpdf --password=mypassword --decrypt encrypted.pdf decrypted.pdf

pdftk (if available)

# Merge
pdftk file1.pdf file2.pdf cat output merged.pdf

# Split
pdftk input.pdf burst

# Rotate
pdftk input.pdf rotate 1east output rotated.pdf

Common Tasks

Extract Text from 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

# Create watermark (or load existing)
watermark = PdfReader("watermark.pdf").pages[0]

# Apply to all pages
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)

Extract Images

# Using pdfimages (poppler-utils)
pdfimages -j input.pdf output_prefix

# This extracts all images as output_prefix-000.jpg, output_prefix-001.jpg, etc.

Password Protection

from pypdf import PdfReader, PdfWriter

reader = PdfReader("input.pdf")
writer = PdfWriter()

for page in reader.pages:
    writer.add_page(page)

# Add password
writer.encrypt("userpassword", "ownerpassword")

with open("encrypted.pdf", "wb") as output:
    writer.write(output)

Quick Reference

Examples

Example 1: Extract tables from PDF report

User: "Pull the tables out of this quarterly report PDF"
→ Opens PDF with pdfplumber
→ Extracts tables, converts to pandas DataFrame
→ Exports to Excel file with clean formatting

Example 2: Merge multiple PDFs

User: "Combine these three contracts into one PDF"
→ Uses pypdf to read all input files
→ Adds pages sequentially to new writer
→ Saves merged document to output path

Example 3: Fill out a PDF form

User: "Fill in this tax form with my info"
→ Reads forms.md for form-filling workflow
→ Uses pdf-lib to populate form fields
→ Saves completed PDF with flattened form data

Next Steps

• For advanced pypdfium2 usage, see reference.md
• For JavaScript libraries (pdf-lib), see reference.md
• If you need to fill out a PDF form, follow the instructions in forms.md
• For troubleshooting guides, see reference.md