pdf-official
Verifiedby sickn33 · Updated Apr 16, 2026
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.
See It In Action
Let me start by finding the PDF files and understanding the project structure.
Found the 3 PDFs. Let me read them all and the skill guide to determine the best extraction approach.
I have all three PDFs. Let me use pdfplumber to programmatically extract the tables and text, then consolidate everything into a single report with audit-ready extracts.
Let me install the dependencies and run extraction.
Python venv mismatch — pip installed to conda's 3.13 but the active python is a 3.12 venv. Let me install into the correct environment.
Text extraction worked perfectly on all 3 (including the scanned Q3). The tables are text-formatted (not PDF table objects), so pdfplumber's table detector found 0 structured tables. I'll parse the revenue lines from the extracted text instead.
All 3 PDFs extracted cleanly. Here's the summary for the board:
Acme Corporation - Q1-Q3 2025 Revenue Consolidated
Quarterly Totals (all sum checks passed)
| Quarter | Revenue | YoY | QoQ |
|---|---|---|---|
| Q1 2025 | $4,540,000 | +14.2% | -- |
| Q2 2025 | $5,130,000 | +16.8% | +13.0% |
| Q3 2025 | $5,720,000 | +18.5% | +11.5% |
| YTD | $15,390,000 |
By Category (YTD)
- Enterprise Software: $8.3M (54.0%) -- largest segment
- Cloud Services: $5.0M (32.2%) -- fastest YoY growth (22-37%)
- Professional Services: $2.1M (13.8%)
By Region (YTD)
- North America: $7.7M (49.8%)
- EMEA: $4.8M (31.1%)
- APAC: $2.9M (19.1%) -- highest growth rates across all categories
Key board notes from reports
- Q3 was a record quarter driven by enterprise renewals + cloud expansion
- APAC Cloud Services growth at +37.1% is the standout segment
- Board approved FY2026 EMEA investment plan
- Q3 report was scanned from a printed copy (text extracted cleanly)
Audit artifacts
consolidated_revenue.csv-- all 27 line items with source file traceability- Full text extracts from all 3 PDFs printed above for audit comparison
- Integrity checks: all 3 quarterly sums match reported totals exactly
External Tools
| Tool | Type |
|---|---|
| python3 | binary |
| pip | binary |
Permissions
| Scope | Description |
|---|---|
| filesystem:read | |
| filesystem:write | |
| process:spawn |
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}:\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 |
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
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
FAQ
What does pdf-official do?
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.
When should I use pdf-official?
Use it when you need a repeatable workflow that produces structured table, source code.
What does pdf-official output?
In the evaluated run it produced structured table, source code.
How do I install or invoke pdf-official?
Ask the agent to use this skill when the task matches its documented workflow.
Which agents does pdf-official support?
Agent support is inferred from the source, but not explicitly declared.
What tools, channels, or permissions does pdf-official need?
It uses python3, pip; channels commonly include table, code; permissions include filesystem:read, filesystem:write, process:spawn.
Is pdf-official safe to install?
Static analysis marked this skill as medium risk; review side effects and permissions before enabling it.
How is pdf-official different from an MCP or plugin?
A skill packages instructions and workflow conventions; tools, MCP servers, and plugins are dependencies the skill may call during execution.
Does pdf-official outperform not using a skill?
About pdf-official
When to use pdf-official
When you need to merge, split, rotate, encrypt, or watermark PDF files programmatically. When you need to extract text or tables from PDF documents into local files for analysis. When you need to generate simple reports or PDFs from code.
When pdf-official is not the right choice
When the task requires a cloud connector or external document platform integration. When you only need general guidance about PDFs without actually running Python-based processing.
What it produces
Produces structured table and source code.