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Pdf

  • 860 installs
  • 432 repo stars
  • Updated November 11, 2025
  • ailabs-393/ai-labs-claude-skills

pdf is a document-automation skill that reads, analyzes, and fills PDF forms using bundled Python scripts for developers who need reliable PDF handling inside Claude or Cursor agent workflows.

About

pdf is an ailabs-393/ai-labs-claude-skills workflow that enforces a ordered pipeline before any code is written: first detect fillable fields with `python scripts/check_fillable_fields <file.pdf>`, then branch into fillable or non-fillable handling paths. For fillable PDFs, `python scripts/extract_form_field_info.py` emits JSON listing field IDs and page metadata for programmatic completion. Developers reach for pdf when agents must ingest contracts, tax forms, or application PDFs, extract structured field data, or auto-fill forms as part of backend or automation features. The skill keeps PDF logic in tested scripts rather than ad-hoc library calls inside generated code.

  • Checks whether a PDF contains fillable form fields before proceeding
  • Extracts structured field metadata including bounding boxes, types, and options into JSON
  • Provides separate handling paths for fillable versus non-fillable PDFs
  • Runs via simple Python scripts from the project directory
  • Critical ordered steps that prevent skipping ahead to code generation

Pdf by the numbers

  • 860 all-time installs (skills.sh)
  • +6 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #319 of 2,719 Automation & Workflows skills by installs in the Skillselion catalog
  • Security screen: HIGH risk (skills.sh audit)
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs860
repo stars432
Security audit1 / 3 scanners passed
Last updatedNovember 11, 2025
Repositoryailabs-393/ai-labs-claude-skills

How do agents fill PDF forms programmatically?

Let their coding agent reliably read, analyze, and fill PDF forms and documents as part of automated workflows.

Who is it for?

Developers automating document workflows who need agents to reliably classify, extract, and fill PDF forms without skipping validation steps.

Skip if: Developers who only need one-off PDF viewing or simple text extraction without form-field detection and fill workflows.

When should I use this skill?

The user asks to read, analyze, fill, or extract data from PDF documents or forms in an automated agent workflow.

What you get

Field metadata JSON, completed PDF forms, and fillable-vs-non-fillable classification

  • field_info.json field metadata
  • Completed filled PDF
  • Fillable-field classification result

By the numbers

  • Bundles at least 2 Python scripts: check_fillable_fields and extract_form_field_info.py

Files

SKILL.mdMarkdownGitHub ↗

PDF Processing Guide

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

TaskBest ToolCommand/Code
Merge PDFspypdfwriter.add_page(page)
Split PDFspypdfOne page per file
Extract textpdfplumberpage.extract_text()
Extract tablespdfplumberpage.extract_tables()
Create PDFsreportlabCanvas or Platypus
Command line mergeqpdfqpdf --empty --pages ...
OCR scanned PDFspytesseractConvert to image first
Fill PDF formspdf-lib or pypdf (see forms.md)See forms.md

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

Related skills

Forks & variants (10)

Pdf has 10 known copies in the catalog totaling 283 installs. They canonicalize to this original listing.

How it compares

Pick pdf over generic document skills when the task requires form-field detection, JSON field extraction, and ordered fillable-vs-non-fillable branching rather than plain text reading.

FAQ

What is the first step when filling a PDF with the pdf skill?

The pdf skill requires running `python scripts/check_fillable_fields <file.pdf>` from the skill directory before writing any code. The result determines whether to follow the fillable-fields or non-fillable-fields workflow path.

How does the pdf skill extract form field data?

For fillable PDFs, the pdf skill runs `python scripts/extract_form_field_info.py <input.pdf> <field_info.json>`, producing JSON with field_id entries and page metadata for each form field.

Is Pdf safe to install?

skills.sh reports 1 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

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