PDF Processing Guide Skill

PDF Processing Guide

🎯 Load Full PAI Context

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

read ~/.opencode/skills/PAI/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

| 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 | | Command line merge | qpdf | qpdf --empty --pages ... | | OCR scanned PDFs | pytesseract | Convert to image first | | Fill PDF forms | pdf-lib or pypdf (see forms.md) | See forms.md |

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

Agent Skills: PDF Processing Guide

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