PD

pdf-processing-pro

Automates PDF data extraction and form completion with built-in validation and error handling.

Install

mkdir -p .claude/skills/pdf-processing-pro && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/87" && unzip -o skill.zip -d .claude/skills/pdf-processing-pro && rm skill.zip

Installs to .claude/skills/pdf-processing-pro

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
247 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Extract text and tabular data from documents
  • Analyze and detect PDF form fields
  • Validate and fill PDF forms with data
  • Perform OCR on scanned PDFs
  • Handle batch PDF processing workflows

How it works

Wraps PDF processing libraries in custom scripts that include built-in validation, logging, and error-handling routines for production pipelines.

Inputs & outputs

You give it
PDF document and data file or extraction requirement
You get back
Extracted CSV/JSON, filled PDF files, or validation report

When to use pdf-processing-pro

  • Extract tabular data from invoices
  • Automate PDF form filling with validation
  • OCR text extraction from scanned documents

About this skill

PDF Processing Pro

Production-ready PDF processing toolkit with pre-built scripts, comprehensive error handling, and support for complex workflows.

Quick start

Extract text from PDF

import pdfplumber

with pdfplumber.open("document.pdf") as pdf:
    text = pdf.pages[0].extract_text()
    print(text)

Analyze PDF form (using included script)

python scripts/analyze_form.py input.pdf --output fields.json
# Returns: JSON with all form fields, types, and positions

Fill PDF form with validation

python scripts/fill_form.py input.pdf data.json output.pdf
# Validates all fields before filling, includes error reporting

Extract tables from PDF

python scripts/extract_tables.py report.pdf --output tables.csv
# Extracts all tables with automatic column detection

Features

✅ Production-ready scripts

All scripts include:

  • Error handling: Graceful failures with detailed error messages
  • Validation: Input validation and type checking
  • Logging: Configurable logging with timestamps
  • Type hints: Full type annotations for IDE support
  • CLI interface: --help flag for all scripts
  • Exit codes: Proper exit codes for automation

✅ Comprehensive workflows

  • PDF Forms: Complete form processing pipeline
  • Table Extraction: Advanced table detection and extraction
  • OCR Processing: Scanned PDF text extraction
  • Batch Operations: Process multiple PDFs efficiently
  • Validation: Pre and post-processing validation

Advanced topics

PDF Form Processing

For complete form workflows including:

  • Field analysis and detection
  • Dynamic form filling
  • Validation rules
  • Multi-page forms
  • Checkbox and radio button handling

See FORMS.md

Table Extraction

For complex table extraction:

  • Multi-page tables
  • Merged cells
  • Nested tables
  • Custom table detection
  • Export to CSV/Excel

See TABLES.md

OCR Processing

For scanned PDFs and image-based documents:

  • Tesseract integration
  • Language support
  • Image preprocessing
  • Confidence scoring
  • Batch OCR

See OCR.md

Included scripts

Form processing

analyze_form.py - Extract form field information

python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]

fill_form.py - Fill PDF forms with data

python scripts/fill_form.py input.pdf data.json output.pdf [--validate]

validate_form.py - Validate form data before filling

python scripts/validate_form.py data.json schema.json

Table extraction

extract_tables.py - Extract tables to CSV/Excel

python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]

Text extraction

extract_text.py - Extract text with formatting preservation

python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]

Utilities

merge_pdfs.py - Merge multiple PDFs

python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf

split_pdf.py - Split PDF into individual pages

python scripts/split_pdf.py input.pdf --output-dir pages/

validate_pdf.py - Validate PDF integrity

python scripts/validate_pdf.py input.pdf

Common workflows

Workflow 1: Process form submissions

# 1. Analyze form structure
python scripts/analyze_form.py template.pdf --output schema.json

# 2. Validate submission data
python scripts/validate_form.py submission.json schema.json

# 3. Fill form
python scripts/fill_form.py template.pdf submission.json completed.pdf

# 4. Validate output
python scripts/validate_pdf.py completed.pdf

Workflow 2: Extract data from reports

# 1. Extract tables
python scripts/extract_tables.py monthly_report.pdf --output data.csv

# 2. Extract text for analysis
python scripts/extract_text.py monthly_report.pdf --output report.txt

Workflow 3: Batch processing

import glob
from pathlib import Path
import subprocess

# Process all PDFs in directory
for pdf_file in glob.glob("invoices/*.pdf"):
    output_file = Path("processed") / Path(pdf_file).name

    result = subprocess.run([
        "python", "scripts/extract_text.py",
        pdf_file,
        "--output", str(output_file)
    ], capture_output=True)

    if result.returncode == 0:
        print(f"✓ Processed: {pdf_file}")
    else:
        print(f"✗ Failed: {pdf_file} - {result.stderr}")

Error handling

All scripts follow consistent error patterns:

# Exit codes
# 0 - Success
# 1 - File not found
# 2 - Invalid input
# 3 - Processing error
# 4 - Validation error

# Example usage in automation
result = subprocess.run(["python", "scripts/fill_form.py", ...])

if result.returncode == 0:
    print("Success")
elif result.returncode == 4:
    print("Validation failed - check input data")
else:
    print(f"Error occurred: {result.returncode}")

Dependencies

All scripts require:

pip install pdfplumber pypdf pillow pytesseract pandas

Optional for OCR:

# Install tesseract-ocr system package
# macOS: brew install tesseract
# Ubuntu: apt-get install tesseract-ocr
# Windows: Download from GitHub releases

Performance tips

  • Use batch processing for multiple PDFs
  • Enable multiprocessing with --parallel flag (where supported)
  • Cache extracted data to avoid re-processing
  • Validate inputs early to fail fast
  • Use streaming for large PDFs (>50MB)

Best practices

  1. Always validate inputs before processing
  2. Use try-except in custom scripts
  3. Log all operations for debugging
  4. Test with sample PDFs before production
  5. Set timeouts for long-running operations
  6. Check exit codes in automation
  7. Backup originals before modification

Troubleshooting

Common issues

"Module not found" errors:

pip install -r requirements.txt

Tesseract not found:

# Install tesseract system package (see Dependencies)

Memory errors with large PDFs:

# Process page by page instead of loading entire PDF
with pdfplumber.open("large.pdf") as pdf:
    for page in pdf.pages:
        text = page.extract_text()
        # Process page immediately

Permission errors:

chmod +x scripts/*.py

Getting help

All scripts support --help:

python scripts/analyze_form.py --help
python scripts/extract_tables.py --help

For detailed documentation on specific topics, see:

When not to use it

  • Simple static PDF viewing tasks
  • Browser-based PDF interactions

Prerequisites

pdfplumberPython 3

Limitations

  • Scanned PDFs require OCR preprocessing
  • Complex nested tables may require custom logic
  • Performance depends on PDF complexity

How it compares

It provides production-hardened scripts (exit codes, type hints) instead of simple ad-hoc extraction snippets.

Compared to similar skills

pdf-processing-pro side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
pdf-processing-pro (this skill)179moReviewIntermediate
pdf04moReviewIntermediate
python-repl64moReviewBeginner
math-router66moReviewBeginner

Try saying

Example prompts that trigger this skill in your AI assistant.

software-architecture

davila7

Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.

333868

planning-with-files

davila7

Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.

233106

telegram-bot-builder

davila7

Expert in building Telegram bots that solve real problems - from simple automation to complex AI-powered bots. Covers bot architecture, the Telegram Bot API, user experience, monetization strategies, and scaling bots to thousands of users. Use when: telegram bot, bot api, telegram automation, chat bot telegram, tg bot.

106130

scroll-experience

davila7

Expert in building immersive scroll-driven experiences - parallax storytelling, scroll animations, interactive narratives, and cinematic web experiences. Like NY Times interactives, Apple product pages, and award-winning web experiences. Makes websites feel like experiences, not just pages. Use when: scroll animation, parallax, scroll storytelling, interactive story, cinematic website.

101142

humanizer

davila7

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

90175

game-development

davila7

Game development orchestrator. Routes to platform-specific skills based on project needs.

70195

You might also like

pdf

sam-cogan

Read, extract, create, merge, split, rotate, watermark, encrypt, OCR, or fill forms in PDF files. Triggers: any mention of \".pdf\", \"PDF\", or requests to extract text/tables from PDFs, combine/merge PDFs, split pages, create new PDFs, fill PDF forms, add watermarks, encrypt/decrypt, extract image

00

python-repl

gptme

Interactive Python REPL automation with common helpers and best practices

6102

math-router

parcadei

Deterministic router for math cognitive stack - maps user intent to exact CLI commands

619

optimizing-gas-fees

jeremylongshore

Optimize blockchain gas costs by analyzing prices, patterns, and timing. Use when checking gas prices, estimating costs, or finding optimal windows. Trigger with phrases like "gas prices", "optimize gas", "transaction cost", "when to transact".

11

tooluniverse-sdk

mims-harvard

Build AI scientist systems using ToolUniverse Python SDK for scientific research. Use when users need to access 1000++ scientific tools through Python code, create scientific workflows, perform drug discovery, protein analysis, genomics analysis, literature research, or any computational biology task. Triggers include requests to use scientific tools programmatically, build research pipelines, analyze biological data, search literature, predict drug properties, or create AI-powered scientific workflows.

01

airflow

ComeOnOliver

Apache Airflow lets you define workflows as Directed Acyclic Graphs (DAGs) in Python. Each DAG consists of tasks connected by dependencies, scheduled and monitored via a web UI.

00

Search skills

Search the agent skills registry