skill 本地 Skill CC-BY-4.0

PDF Processing Pro Skill

處理 PDF 文字擷取、建立、表單與檔案分析任務。

啟用時機

當你需要 PDF Processing Pro 的工作流程時使用。

適合使用情境

  • 需要處理「處理 PDF 文字擷取、建立、表單與檔案分析任務」這類任務。
  • 想直接閱讀或複製 PDF Processing Pro 的完整 SKILL.md。
  • 需要從 skill repo 的本地落地版本追溯來源與檔案位置。

Skill 檔案

  • skills/pdf-processing-pro/pdf-processing-pro/SKILL.md

工作流程

  1. 先確認這個 Skill 的啟用時機與輸入需求。
  2. 閱讀原始 SKILL.md,確認它要求的工具、檔案、API key 或環境限制。
  3. 用小型真實任務測試輸出是否符合預期。
  4. 確認結果穩定後,再把它放進日常 Agent 工作流程。

使用注意事項

  • 這筆資料來自 skill repo 的本地落地版,與 awesome-agent-skills 上游索引不同;此頁保留完整 SKILL.md 供追溯。

來源

原始名稱:PDF Processing Pro

處理 PDF 文字擷取、建立、表單與檔案分析任務。

software-engineering-prompt-repos/skill/skills/pdf-processing-pro/pdf-processing-pro/SKILL.md

開啟來源

這個 Skill 在做什麼

處理 PDF 文字擷取、建立、表單與檔案分析任務。

來源整理

這筆資料來自 skill repo 的本地落地版本。awesome-agent-skills 是上游索引;skill repo 則是把部分技能抓回來、整理成技能商店與本地可追溯檔案的版本。

使用前先確認

請先看原始 SKILL.md 的工具、環境變數、參考檔與安全限制,再放進自己的 Agent 工作流程。

SKILL.md 內容
---
name: PDF Processing Pro
description: 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.
---

# 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