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.

564 stars

Best use case

pdf-processing-pro is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using pdf-processing-pro should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/pdf-processing-pro/SKILL.md --create-dirs "https://raw.githubusercontent.com/beita6969/ScienceClaw/main/skills/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

Related Skills

signal-processing

564
from beita6969/ScienceClaw

Performs signal processing tasks including spectral analysis (FFT), digital filtering, time-frequency decomposition, noise reduction, and modulation/demodulation; trigger when users discuss waveforms, frequency spectra, filters, or time series in engineering contexts.

post-processing

564
from beita6969/ScienceClaw

Extract, analyze, and visualize simulation output data. Use for field extraction, time series analysis, line profiles, statistical summaries, derived quantity computation, result comparison to references, and automated report generation from simulation results.

pdf-processing

564
from beita6969/ScienceClaw

Extract text and tables from PDF files, fill forms, merge documents. Use when working with PDF files or when the user mentions PDFs, forms, or document extraction.

xurl

564
from beita6969/ScienceClaw

A CLI tool for making authenticated requests to the X (Twitter) API. Use this skill when you need to post tweets, reply, quote, search, read posts, manage followers, send DMs, upload media, or interact with any X API v2 endpoint.

xlsx

564
from beita6969/ScienceClaw

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

writing

564
from beita6969/ScienceClaw

No description provided.

world-bank-data

564
from beita6969/ScienceClaw

World Bank Open Data API for development indicators. Use when: user asks about GDP, population, poverty, health, or education statistics by country. NOT for: real-time financial data or stock prices.

wikipedia-search

564
from beita6969/ScienceClaw

Search and fetch structured content from Wikipedia using the MediaWiki API for reliable, encyclopedic information

wikidata-knowledge

564
from beita6969/ScienceClaw

Query Wikidata for structured knowledge using SPARQL and entity search. Use when: (1) finding structured facts about entities (people, places, organizations), (2) querying relationships between entities, (3) cross-referencing external identifiers (Wikipedia, VIAF, GND, ORCID), (4) building knowledge graphs from linked data. NOT for: full-text article content (use Wikipedia API), scientific literature (use semantic-scholar), geospatial data (use OpenStreetMap).

weather

564
from beita6969/ScienceClaw

Get current weather and forecasts via wttr.in or Open-Meteo. Use when: user asks about weather, temperature, or forecasts for any location. NOT for: historical weather data, severe weather alerts, or detailed meteorological analysis. No API key needed.

wacli

564
from beita6969/ScienceClaw

Send WhatsApp messages to other people or search/sync WhatsApp history via the wacli CLI (not for normal user chats).

voice-call

564
from beita6969/ScienceClaw

Start voice calls via the OpenClaw voice-call plugin.