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wu-uk

pdf

by wu-uk · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install invoice-fraud-detection-pdf
Description
Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs...
README (SKILL.md)

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}:\
"
    text += pytesseract.image_to_string(image)
    text += "\
\
"

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

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
Usage Guidance
What to consider before installing/using this skill: - The code and README appear to implement a legitimate PDF toolkit, but the package does not declare the many Python packages and system tools it uses (pypdf, pdfplumber, pdf2image, pytesseract, reportlab, pypdfium2, pillow) nor CLI tools (poppler-utils: pdftotext/pdfimages, qpdf, pdftk, tesseract). Make sure the runtime has these dependencies or the scripts will fail. - The bundle contains executable Python scripts. Running them will execute code on your agent/environment — review the scripts (they are included) and run them in a sandbox or test environment first, especially if you will process sensitive PDFs. - One script monkeypatches an internal pypdf method (fill_fillable_fields.py). That is likely a workaround, but it changes library behavior at runtime and could have unintended side effects; inspect and test it. - The LICENSE is restrictive (claims Anthropic ownership and forbids extracting/copying materials). Ensure you have the legal right to use these files in your environment. - There is no network activity in the scripts as provided, but processing user documents can expose sensitive data locally — do not feed private documents unless you trust the environment. Consider running on non-sensitive samples first and verify outputs. - If you plan to use it, add explicit dependency installation instructions (or a requirements.txt/venv) and prefer running in an isolated environment (container or VM).
Capability Analysis
Type: OpenClaw Skill Name: invoice-fraud-detection-pdf Version: 0.1.0 The bundle is a comprehensive and well-documented toolkit for PDF processing, including text extraction, form filling, and document manipulation. It utilizes standard Python libraries such as pypdf, pdfplumber, and reportlab, and provides clear instructions for an AI agent to handle both fillable and non-fillable forms through a structured workflow (forms.md). No evidence of malicious intent, data exfiltration, or harmful prompt injection was found; even the monkeypatch in scripts/fill_fillable_fields.py is explicitly documented as a fix for a known library bug.
Capability Assessment
Purpose & Capability
The name/description match the included scripts and SKILL.md: the bundle provides PDF reading, form extraction/filling, image conversion, annotation, and table extraction. However, the skill declares no required binaries/env or install spec despite using many third-party Python libraries and CLI tools (pypdf, pdfplumber, pdf2image, pytesseract, reportlab, pypdfium2, PIL, poppler-utils tools like pdftotext/pdfimages, qpdf, pdftk). Also the registry metadata said "No install spec — instruction-only" while the archive actually contains executable Python scripts, which is an inconsistency.
Instruction Scope
SKILL.md and forms.md instruct only local PDF processing steps and running the included Python scripts. The runtime instructions/ scripts operate on local files (PDFs, generated PNGs, JSON field descriptors) and do not call any external network endpoints or request unrelated system files or credentials. They do, however, require the user/agent to open and process arbitrary PDF files (expected for this tool).
Install Mechanism
There is no install spec (good that nothing is downloaded at install time), but the code bundle contains multiple Python scripts that will be executed; the package relies on many external Python packages and system utilities which are not declared or provided. Because the scripts are executed locally, they can run arbitrary code in the agent's environment. There is no remote download URL in the install steps, so high-risk remote-install indicators are absent, but the lack of dependency declaration is a practical and security concern.
Credentials
The skill requests no environment variables or credentials (none declared). That is proportionate for a PDF processing toolkit. Note: the LICENSE file is proprietary and restrictive (disallows extracting materials or keeping copies outside the Services); this is a legal/operational concern but not an environment-credential leak.
Persistence & Privilege
Flags indicate the skill is not forced-always and model invocation is allowed (normal). The skill does not request persistent system-wide changes, does not modify other skills, and does not request elevated privileges.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install invoice-fraud-detection-pdf
  3. After installation, invoke the skill by name or use /invoice-fraud-detection-pdf
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Bulk publish from all-task-skills-dedup
Metadata
Slug invoice-fraud-detection-pdf
Version 0.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is pdf?

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs... It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.

How do I install pdf?

Run "/install invoice-fraud-detection-pdf" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is pdf free?

Yes, pdf is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does pdf support?

pdf is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created pdf?

It is built and maintained by wu-uk (@wu-uk); the current version is v0.1.0.

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