
processing-pdf
Use when the user needs to extract data from PDFs, work with scanned documents, or manipulate PDF files. Triggers include: "extract text from PDF", "convert PDF to text/CSV/images", "scan/OCR this document", "merge/split/rotate PDF", "fill PDF form", "PDF is blank/empty" (likely scanned), or any mention of .pdf files requiring data extraction or transformation. Also use for invoices, receipts, forms, contracts, reports, or any document where structured data (text, tables, form fields) needs to be extracted.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/osmontero/opencode-skills --skill processing-pdf- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads processing-pdf automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
PDF Processing
Process PDF files using command-line tools and Python libraries. For scanned PDFs, convert pages to images and have the LLM read them using its built-in image understanding.
Prerequisites
Before running any Python scripts, activate the opencode virtual environment:
source ~/.local/opencode-venv/bin/activate
Then use python3 scripts/... normally.
Available Tools
| Tool | Command | Use For |
|---|---|---|
pdf-extractor agent | Global agent (dispatch via subagent) | Full PDF extraction (all pages, all data, structured folder tree) |
pdftotext | System (Poppler) | Quick text extraction |
pdfinfo | System (Poppler) | Metadata, page count |
pypdf | Python (venv) | Merge, split, rotate |
pdfplumber | Python (venv) | Table extraction, detailed text |
to_images.py | Python script (venv) | Convert pages to PNG images |
Decision Guide
Need to process a PDF?
│
├─ Extract everything from a PDF?
│ └─ Dispatch the `pdf-extractor` agent.
│ It converts all pages to images, reads each one, and stores
│ per-page results in extracted_data/<pdf_name>/page_NNN/content.md
│ along with images and a summary.
│
├─ Quick text from a normal PDF?
│ ├─ Simple: pdftotext input.pdf output.txt
│ └─ With page numbers: python3 scripts/extract_text.py input.pdf
│
├─ Extract tables?
│ └─ python3 scripts/extract_tables.py input.pdf -o ./tables/
│
├─ Fill a form?
│ ├─ Check fields: python3 scripts/check_forms.py input.pdf
│ └─ Fill: python3 scripts/fill_form.py input.pdf fields.json output.pdf
│
├─ Read a scanned PDF (quick)?
│ ├─ Convert: python3 scripts/to_images.py scanned.pdf -o ./pages/ --dpi 200
│ └─ Read the images and extract what you need
│
├─ Merge/Split/Rotate?
│ └─ See pypdf examples below
│
└─ Large file (>50MB)?
├─ Quick text: pdftotext (fastest)
└─ Page ranges: pdftotext -f N -l M input.pdf
Full PDF Extraction
For complete extraction of all data from a PDF (text, tables, forms, structure), dispatch the pdf-extractor agent. It:
- Converts all pages to PNG images
- Reads each image using LLM vision
- Extracts text, tables, key facts, form fields, and notes
- Per-page output in
extracted_data/<pdf_name>/page_NNN/:page_NNN.png— the page imagecontent.md— all text and extracted facts as markdown- Other LLM-legible files as needed
- Creates
summary.mdwith document-level overview
When to use the extractor agent
- Multi-page documents where you need all the data
- Scanned PDFs or mixed scanned/digital PDFs
- Documents with complex layouts (tables, columns, forms)
- When you need a structured, browsable folder tree of results
Quick extraction (no agent)
For a single page or a quick glance, use the manual steps below.
Reading Scanned PDFs (Quick, No Agent)
When a PDF is scanned (no selectable text), convert its pages to images and let the LLM read them.
Step 1: Detect if PDF is scanned
pdftotext document.pdf - | head -20
If output is empty or whitespace, the PDF is scanned.
Step 2: Convert pages to images
# All pages at 200 DPI (sufficient for most documents)
python3 scripts/to_images.py document.pdf -o ./pdf-pages/ --dpi 200
# Higher quality for handwritten or low-quality scans
python3 scripts/to_images.py document.pdf -o ./pdf-pages/ --dpi 300
Step 3: Read the images
Reference the generated PNG files directly — the LLM can read them natively. Ask it to extract text, tables, fields, or answer questions about the document content.
Step 4: Clean up
rm -rf ./pdf-pages/
Tips for scanned PDFs
- 200 DPI works for most documents
- 300 DPI for handwritten content or blurry scans
- For large PDFs, convert pages in batches (use pypdf to split first, then convert)
- Always clean up the generated image directory after reading
Text Extraction
Quick extraction (pdftotext)
# Simple extraction
pdftotext input.pdf output.txt
# Single page
pdftotext -f 3 -l 3 input.pdf page3.txt
# With layout preservation
pdftotext -layout input.pdf output.txt
# Page range
pdftotext -f 5 -l 10 input.pdf pages_5_10.txt
With page numbers (script)
python3 scripts/extract_text.py input.pdf
Get PDF info
pdfinfo input.pdf
Table Extraction
Script (recommended)
python3 scripts/extract_tables.py input.pdf -o ./tables/
Python (inline)
import pdfplumber
import csv
with pdfplumber.open("input.pdf") as pdf:
for i, page in enumerate(pdf.pages):
tables = page.extract_tables()
for j, table in enumerate(tables):
with open(f"page{i+1}_table{j+1}.csv", "w", newline="") as f:
writer = csv.writer(f)
for row in table:
writer.writerow([cell or "" for cell in row])
Form Handling
Check for fillable fields
python3 scripts/check_forms.py input.pdf
Fill a form
python3 scripts/fill_form.py input.pdf fields.json output.pdf
Where fields.json contains:
{
"field_name": "John Smith",
"email": "john@example.com",
"date": "2026-05-04"
}
PDF Manipulation (pypdf)
Merge PDFs
from pypdf import PdfReader, PdfWriter
writer = PdfWriter()
for pdf_file in ["file1.pdf", "file2.pdf", "file3.pdf"]:
reader = PdfReader(pdf_file)
for page in reader.pages:
writer.add_page(page)
with open("merged.pdf", "wb") as f:
writer.write(f)
Split into individual pages
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
for i, page in enumerate(reader.pages):
writer = PdfWriter()
writer.add_page(page)
with open(f"page_{i+1:03d}.pdf", "wb") as f:
writer.write(f)
Rotate pages
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
writer = PdfWriter()
for page in reader.pages:
page.rotate(90) # 90, 180, or 270 degrees
writer.add_page(page)
with open("rotated.pdf", "wb") as f:
writer.write(f)
Remove pages
from pypdf import PdfReader, PdfWriter
reader = PdfReader("input.pdf")
writer = PdfWriter()
pages_to_keep = {0, 1, 4, 5} # 0-indexed
for i, page in enumerate(reader.pages):
if i in pages_to_keep:
writer.add_page(page)
with open("trimmed.pdf", "wb") as f:
writer.write(f)
Metadata
python3 scripts/metadata.py input.pdf
Convert to Images
python3 scripts/to_images.py input.pdf --dpi 200
Large Files
For large PDFs (>50MB):
- Use
pdftotextfor quick extraction (faster than Python) - Process pages in batches with
pdfplumber - Use
-fand-lflags withpdftotextfor specific page ranges
Writing Large Output Files
If extracting text from a very large PDF, write the output incrementally (~1000 tokens per edit) rather than in a single pass.
Common Patterns
Search for text in a PDF
pdftotext input.pdf - | grep -n "search term"
Compare two PDFs (text diff)
pdftotext doc1.pdf - > /tmp/doc1.txt
pdftotext doc2.pdf - > /tmp/doc2.txt
diff /tmp/doc1.txt /tmp/doc2.txt
Edge Cases
Encrypted PDFs
from pypdf import PdfReader
reader = PdfReader("encrypted.pdf")
if reader.is_encrypted:
reader.decrypt("") # Try empty password first
Corrupted or Invalid PDFs
try:
with pdfplumber.open("file.pdf") as pdf:
# process...
except Exception as e:
print(f"Error processing PDF: {e}")
Very Large PDFs (>100MB)
- Use
pdftotextfor speed - Process in page batches with pdfplumber
- Avoid loading entire file into memory
Mixed Content (Some pages scanned, some not)
- First try standard extraction (
pdftotext) - Check which pages returned empty text
- Convert only those pages to images and have the LLM read them
FAQ
What does the processing-pdf skill do?
Use when the user needs to extract data from PDFs, work with scanned documents, or manipulate PDF files. Triggers include: "extract text from PDF", "convert PDF to text/CSV/images", "scan/OCR this document", "merge/split/rotate PDF", "fill PDF form", "PDF is blank/empty" (likely scanned), or any mention of .pdf files requiring data extraction or transformation. Also use for invoices, receipts, forms, contracts, reports, or any document where structured data (text, tables, form fields) needs to be extracted.
How do I install processing-pdf?
Run npx skills add https://github.com/osmontero/opencode-skills --skill processing-pdf in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/processing-pdf/ (personal) or .claude/skills/processing-pdf/ (project).
Which AI agents can use processing-pdf?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is processing-pdf safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains processing-pdf?
It is published by osmontero in osmontero/opencode-skills. It has 86 recorded installs.
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