PDF-Text-Extractor

Extract text from PDFs with OCR support. Zero external dependencies (except PDF.js).

Quick Start

# Install
clawhub install pdf-text-extractor

# Extract text from PDF
cd ~/.openclaw/skills/pdf-text-extractor
node index.js extractText '{"pdfPath":"./document.pdf","options":{"outputFormat":"text"}}'

Usage Examples

Extract to Text

const result = await extractText({
  pdfPath: './invoice.pdf',
  options: { outputFormat: 'text' }
});

console.log(result.text);

Extract to JSON with Metadata

const result = await extractText({
  pdfPath: './contract.pdf',
  options: {
    outputFormat: 'json',
    includeMetadata: true
  }
});

console.log(result.metadata);
console.log(`Words: ${result.wordCount}`);

Batch Process Multiple PDFs

const results = await extractBatch({
  pdfFiles: [
    './doc1.pdf',
    './doc2.pdf',
    './doc3.pdf'
  ]
});

console.log(`Processed ${results.successCount}/${results.results.length} documents`);

Extract with OCR (Scanned Documents)

const result = await extractText({
  pdfPath: './scanned-doc.pdf',
  options: {
    ocr: true,
    language: 'eng',
    ocrQuality: 'high'
  }
});

console.log(result.text);

Count Words and Stats

const stats = await countWords({
  text: result.text,
  options: { countByPage: true }
});

console.log(`Total words: ${stats.wordCount}`);
console.log(`Pages: ${stats.pageCounts.length}`);
console.log(`Avg per page: ${stats.averageWordsPerPage}`);

Detect Language

const lang = await detectLanguage(text);

console.log(`Language: ${lang.languageName}`);
console.log(`Confidence: ${lang.confidence}%`);

Features

• Text Extraction: Extract text from PDFs without external tools
• OCR Support: Use Tesseract for scanned documents
• Batch Processing: Process multiple PDFs at once
• Multiple Output Formats: Text, JSON, Markdown, HTML
• Word Counting: Accurate word and character counting
• Language Detection: Simple heuristic for common languages
• Metadata Extraction: Title, author, creation date
• Page-by-Page: Extract text with page structure
• Zero Config Required: Works out of the box

Use Cases

Document Digitization

• Convert paper documents to digital text
• Process invoices and receipts
• Digitize contracts and agreements
• Archive physical documents

Content Analysis

• Extract text for analysis tools
• Prepare content for LLM processing
• Clean up scanned documents
• Parse PDF-based reports

Data Extraction

• Extract data from PDF reports
• Parse tables from PDFs
• Pull structured data
• Automate document workflows

Text Processing

• Prepare content for translation
• Clean up OCR output
• Extract specific sections
• Search within PDF content

Configuration

Edit config.json to customize:

{
  "ocr": {
    "enabled": true,
    "defaultLanguage": "eng",
    "quality": "medium"
  },
  "output": {
    "defaultFormat": "text",
    "preserveFormatting": true
  },
  "batch": {
    "maxConcurrent": 3
  }
}

Test

node test.js

Output Formats

Text

Plain text extraction with newlines between pages.

JSON

{
  "text": "Document text here...",
  "pages": 10,
  "wordCount": 1500,
  "charCount": 8500,
  "language": "English",
  "metadata": {
    "title": "Document Title",
    "author": "Author Name",
    "creationDate": "2026-02-04"
  }
}

Performance

Text-Based PDFs

• Speed: ~100ms for 10-page PDF
• Accuracy: 100% (exact text)

OCR Processing

• Speed: ~1-3s per page
• Accuracy: 85-95% (depends on scan quality)

Troubleshooting

PDF Not Parsing

• Check if file is a valid PDF
• Ensure not password-protected
• Verify PDF.js is installed

OCR Low Accuracy

• Ensure document language matches OCR language setting
• Try higher quality setting (slower but more accurate)
• Check scan quality (300 DPI+ recommended)

Slow Processing

• Reduce batch concurrency
• Lower OCR quality for speed
• Process files individually

Dependencies

npm install pdfjs-dist

License

MIT

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Extract text from PDFs. Fast, accurate, ready to use. 🔮