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guohongbin-git

Pdf Cn

by Guohongbin · GitHub ↗ · v1.0.1
cross-platform ✓ Security Clean
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Install in OpenClaw
/install pdf-cn
Description
PDF 文档处理 | PDF Document Processing. 读取、提取、合并、分割 PDF | Read, extract, merge, split PDFs. 支持文本提取、表格识别、注释 | Supports text extraction, table recognition, annotat...
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)

Subscripts and Superscripts

IMPORTANT: Never use Unicode subscript/superscript characters (₀₁₂₃₄₅₆₇₈₉, ⁰¹²³⁴⁵⁶⁷⁸⁹) in ReportLab PDFs. The built-in fonts do not include these glyphs, causing them to render as solid black boxes.

Instead, use ReportLab's XML markup tags in Paragraph objects:

from reportlab.platypus import Paragraph
from reportlab.lib.styles import getSampleStyleSheet

styles = getSampleStyleSheet()

# Subscripts: use \x3Csub> tag
chemical = Paragraph("H\x3Csub>2\x3C/sub>O", styles['Normal'])

# Superscripts: use \x3Csuper> tag
squared = Paragraph("x\x3Csuper>2\x3C/super> + y\x3Csuper>2\x3C/super>", styles['Normal'])

For canvas-drawn text (not Paragraph objects), manually adjust font the size and position rather than using Unicode subscripts/superscripts.

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
Install only if you are comfortable letting the agent run local PDF tools on files you choose. Use copies for important documents, review output paths to avoid overwrites, and only decrypt or process password-protected PDFs when you have permission to access them.
Capability Analysis
Type: OpenClaw Skill Name: pdf-cn Version: 1.0.1 The OpenClaw AgentSkills skill bundle for PDF processing is classified as benign. All Python scripts and documentation (SKILL.md, forms.md, reference.md) are consistently aligned with the stated purpose of reading, extracting, merging, splitting, creating, and filling PDF documents. The skill leverages standard Python libraries (e.g., pypdf, pdfplumber, reportlab, pytesseract, pdf2image) and common command-line utilities (e.g., pdftotext, qpdf, ImageMagick). There is no evidence of intentional malicious behavior such as data exfiltration, backdoor installation, or unauthorized remote control. While the execution of external command-line tools by an AI agent could introduce vulnerabilities if user input is not properly sanitized, the skill itself only provides the capability and examples for legitimate PDF operations, without demonstrating or instructing malicious command construction or prompt injection against the agent.
Capability Assessment
Purpose & Capability
The documented capabilities are coherent with a PDF processing skill: reading, extracting, merging, splitting, rendering, OCR, form filling, creation, repair, encryption, and decryption of user-specified PDFs.
Instruction Scope
The skill includes password removal/decryption examples without an explicit authorization warning, but the examples require the password and do not show cracking, exfiltration, hidden access, or automatic processing.
Install Mechanism
The metadata declares no automatic dependencies, environment changes, background services, or install-time execution.
Credentials
Bundled scripts operate on user-provided PDF, image, and JSON paths and write explicit output files; no network access, credential collection, or broad local indexing was found.
Persistence & Privilege
The skill can create or modify local PDF-related outputs, and one reference example uses in-place qpdf repair, but these are disclosed, command-level, user-directed document operations rather than hidden persistence or privilege escalation.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install pdf-cn
  3. After installation, invoke the skill by name or use /pdf-cn
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
- Added a new metadata file (_meta.json) to the skill. - No changes were made to the functionality or the main documentation.
v1.0.0
PDF document processing | PDF 文档处理,中英文双语
Metadata
Slug pdf-cn
Version 1.0.1
License
All-time Installs 30
Active Installs 30
Total Versions 2
Frequently Asked Questions

What is Pdf Cn?

PDF 文档处理 | PDF Document Processing. 读取、提取、合并、分割 PDF | Read, extract, merge, split PDFs. 支持文本提取、表格识别、注释 | Supports text extraction, table recognition, annotat... It is an AI Agent Skill for Claude Code / OpenClaw, with 2349 downloads so far.

How do I install Pdf Cn?

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

Is Pdf Cn free?

Yes, Pdf Cn is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Pdf Cn support?

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

Who created Pdf Cn?

It is built and maintained by Guohongbin (@guohongbin-git); the current version is v1.0.1.

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