Skill Tester

This is a sample text file for testing the text processor skill.
It contains multiple lines of text with various words and punctuation.
The quick brown fox jumps over the lazy dog.
This sentence contains all 26 letters of the English alphabet.

Some additional content:
- Numbers: 123, 456, 789
- Special characters: !@#$%^&*()
- Mixed case: CamelCase, snake_case, PascalCase

Lorem ipsum dolor sit amet, consectetur adipiscing elit.
Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
Ut enim ad minim veniam, quis nostrud exercitation ullamco.

This file serves as a basic test case for:
1. Word counting functionality
2. Character analysis
3. Line counting
4. Text transformations
5. Statistical analysis

The text processor should handle this content correctly and produce
meaningful statistics and transformations for testing purposes.

name,age,city,country
John Doe,25,New York,USA
Jane Smith,30,London,UK
Bob Johnson,22,Toronto,Canada
Alice Brown,28,Sydney,Australia
Charlie Wilson,35,Berlin,Germany

This CSV file contains sample data with headers and multiple rows.
It can be used to test the text processor's ability to handle
structured data formats and count words across different content types.

The file includes:
- Header row with column names
- Data rows with mixed text and numbers
- Various city and country names
- Different age values for statistical analysis

{
  "file": "assets/sample_text.txt",
  "file_size": 855,
  "total_words": 116,
  "unique_words": 87,
  "total_characters": 855,
  "lines": 19,
  "average_word_length": 4.7,
  "most_frequent": {
    "word": "the",
    "count": 5
  }
}

# Sample Text Processor

A basic text processing skill that demonstrates BASIC tier requirements for the claude-skills ecosystem.

## Quick Start

```bash
# Analyze a text file
python scripts/text_processor.py analyze sample.txt

# Get JSON output
python scripts/text_processor.py analyze sample.txt --format json

# Transform text to uppercase  
python scripts/text_processor.py transform sample.txt --mode upper

# Process multiple files
python scripts/text_processor.py batch text_files/ --verbose
```

## Features

- Word count and text statistics
- Text transformations (upper, lower, title, reverse)
- Batch file processing
- JSON and human-readable output formats
- Comprehensive error handling

## Requirements

- Python 3.7 or later
- No external dependencies (standard library only)

## Usage

See [SKILL.md](SKILL.md) for comprehensive documentation and examples.

## Testing

Sample data files are provided in the `assets/` directory for testing the functionality.

# Text Processor API Reference

## Classes

### TextProcessor

Main class for text processing operations.

#### `__init__(self, encoding: str = 'utf-8')`

Initialize the text processor with specified encoding.

**Parameters:**
- `encoding` (str): Character encoding for file operations. Default: 'utf-8'

#### `analyze_text(self, text: str) -> Dict[str, Any]`

Analyze text and return comprehensive statistics.

**Parameters:**
- `text` (str): Text content to analyze

**Returns:**
- `dict`: Statistics including word count, character count, lines, most frequent word

**Example:**
```python
processor = TextProcessor()
stats = processor.analyze_text("Hello world")
# Returns: {'total_words': 2, 'unique_words': 2, ...}
```

#### `transform_text(self, text: str, mode: str) -> str`

Transform text according to specified mode.

**Parameters:**
- `text` (str): Text to transform
- `mode` (str): Transformation mode ('upper', 'lower', 'title', 'reverse')

**Returns:**
- `str`: Transformed text

**Raises:**
- `ValueError`: If mode is not supported

### OutputFormatter

Static methods for output formatting.

#### `format_json(data: Dict[str, Any]) -> str`

Format data as JSON string.

#### `format_human_readable(data: Dict[str, Any]) -> str`

Format data as human-readable text.

### FileManager

Handles file operations and batch processing.

#### `find_text_files(self, directory: str