pdf-processing-pro

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.

242 stars

Best use case

pdf-processing-pro is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. 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.

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.

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "pdf-processing-pro" skill to help with this workflow task. Context: 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.

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/pdf-processing-pro/SKILL.md --create-dirs "https://raw.githubusercontent.com/aiskillstore/marketplace/main/skills/davila7/pdf-processing-pro/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/pdf-processing-pro/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How pdf-processing-pro Compares

Feature / Agentpdf-processing-proStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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

```python
import pdfplumber

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

### Analyze PDF form (using included script)

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

### Fill PDF form with validation

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

### Extract tables from PDF

```bash
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](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](TABLES.md)

### OCR Processing

For scanned PDFs and image-based documents:
- Tesseract integration
- Language support
- Image preprocessing
- Confidence scoring
- Batch OCR

See [OCR.md](OCR.md)

## Included scripts

### Form processing

**analyze_form.py** - Extract form field information
```bash
python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]
```

**fill_form.py** - Fill PDF forms with data
```bash
python scripts/fill_form.py input.pdf data.json output.pdf [--validate]
```

**validate_form.py** - Validate form data before filling
```bash
python scripts/validate_form.py data.json schema.json
```

### Table extraction

**extract_tables.py** - Extract tables to CSV/Excel
```bash
python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]
```

### Text extraction

**extract_text.py** - Extract text with formatting preservation
```bash
python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]
```

### Utilities

**merge_pdfs.py** - Merge multiple PDFs
```bash
python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf
```

**split_pdf.py** - Split PDF into individual pages
```bash
python scripts/split_pdf.py input.pdf --output-dir pages/
```

**validate_pdf.py** - Validate PDF integrity
```bash
python scripts/validate_pdf.py input.pdf
```

## Common workflows

### Workflow 1: Process form submissions

```bash
# 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

```bash
# 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

```python
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:

```python
# 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:

```bash
pip install pdfplumber pypdf pillow pytesseract pandas
```

Optional for OCR:
```bash
# 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**:
```bash
pip install -r requirements.txt
```

**Tesseract not found**:
```bash
# Install tesseract system package (see Dependencies)
```

**Memory errors with large PDFs**:
```python
# 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**:
```bash
chmod +x scripts/*.py
```

## Getting help

All scripts support `--help`:

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

For detailed documentation on specific topics, see:
- [FORMS.md](FORMS.md) - Complete form processing guide
- [TABLES.md](TABLES.md) - Advanced table extraction
- [OCR.md](OCR.md) - Scanned PDF processing

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