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...

MIT-0 · Free to use, modify, and redistribute. No attribution required.
0 · 1.3k · 22 current installs · 23 all-time installs
byGuohongbin@guohongbin-git
MIT-0
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Suspicious
high confidence
!
Purpose & Capability
The code and SKILL.md implement PDF reading, form extraction, image conversion, OCR, and form-filling — consistent with the description. However, the skill metadata declares no dependencies or required binaries while the instructions and scripts clearly rely on external command-line tools (pdftotext/pdftoppm/pdfimages/qpdf/pdftk/ImageMagick 'magick') and Python packages (pypdf, pdfplumber, pdf2image, pytesseract, reportlab, PIL). The metadata also contains mixed provenance/license signals (LICENSE.txt claims Anthropic ownership and restrictive terms while _meta.json lists MIT and a different author/homepage). These mismatches are a coherence concern.
Instruction Scope
SKILL.md and FORMS.md instruct the agent/user to run local Python scripts and CLI tools that read input PDFs, write output PDFs/images, and create JSON manifests. The instructions do not attempt to read unrelated system files or call external network endpoints. They do, however, instruct use of external tools (ImageMagick, pdftotext, qpdf, pdftk) and recommend installing Python packages; these tool dependencies are not declared in the registry metadata.
Install Mechanism
There is no install spec (lowest installation risk). The skill includes multiple Python scripts in the bundle (so code will be present on disk if installed). This is reasonable for a code-backed skill, but the package does not provide an install/requirements file or declare how to install its Python dependencies or required system binaries — increasing friction and risk of mismatched runtime environments.
Credentials
The skill declares no environment variables or credentials and the scripts do not reference secrets or external credentials. No unexpected credential access was found.
Persistence & Privilege
always is false and there is no install-time modification of other skills or system-wide agent configuration. The skill runs as-invoked and does not request persistent elevated privileges.
What to consider before installing
This skill implements PDF processing and form-filling code, but there are important inconsistencies you should address before trusting it with real data: - Dependency mismatch: The registry lists no required binaries or packages, but SKILL.md/scripts require system tools (pdftotext/pdftoppm/pdfimages/qpdf/pdftk, ImageMagick 'magick') and Python libraries (pypdf, pdfplumber, pdf2image, pytesseract, PIL, reportlab, etc.). Ensure you install these in a controlled environment (virtualenv or container) before running, and verify versions. - Licensing/provenance mismatch: LICENSE.txt claims restrictive Anthropic terms while _meta.json lists MIT and a different author/homepage. Confirm the license and source before redistributing or using in production. - Code audit: The included scripts perform local file I/O and modify PDFs (they do not perform network I/O or handle secrets), but you should still review the code and run it on non-sensitive example files first to validate behavior (especially the form-filling and coordinate transforms). - Run in isolation: Execute the scripts in a sandboxed environment (VM/container) and avoid processing sensitive documents until you are confident in the tool's outputs. If you need automatic agent-driven invocation, consider restricting it until dependencies and provenance are clarified. If these issues are resolved (declare and install dependencies, clarify license/source), the skill otherwise appears coherent with its stated purpose.

Like a lobster shell, security has layers — review code before you run it.

Current versionv1.0.1
Download zip
chinesevk9755psq8g3wpx38hw0wxdaj5s81adgddocumentvk9755psq8g3wpx38hw0wxdaj5s81adgdlatestvk972sp0ewm6qb28da2bvc3gkw581hzgkpdfvk9755psq8g3wpx38hw0wxdaj5s81adgd

License

MIT-0
Free to use, modify, and redistribute. No attribution required.

Runtime requirements

📕 Clawdis

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 <sub> tag
chemical = Paragraph("H<sub>2</sub>O", styles['Normal'])

# Superscripts: use <super> tag
squared = Paragraph("x<super>2</super> + y<super>2</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}:\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

Files

13 total
Select a file
Select a file to preview.

Comments

Loading comments…