SKILL.md•2 kB
---
name: example-data-processor
description: Process CSV data files by cleaning, transforming, and analyzing them. Use this when users need to work with CSV files, clean data, or perform basic data analysis tasks.
---
# Example Data Processor
This skill demonstrates a complete skill structure with scripts, references, and proper documentation.
## What This Skill Does
Processes CSV data files with these capabilities:
- Clean and validate data
- Transform columns
- Generate summary statistics
- Export results
## Usage
### Process a CSV file
To process a CSV file:
```
Process the data in myfile.csv
```
The skill will:
1. Read the CSV file
2. Clean the data (remove nulls, fix formats)
3. Generate statistics
4. Output a summary report
### Custom Processing
For custom processing options:
```
Process sales.csv and group by region
```
## Scripts
**scripts/process_csv.py** - Main data processing script
- Reads CSV files
- Applies transformations
- Generates output
**scripts/fetch_data.py** - API data fetcher (demonstrates uv dependencies)
- Fetches data from APIs using requests
- Beautiful output formatting with rich
- **Auto-installs dependencies** via uv inline metadata (PEP 723)
- No manual pip install needed!
**scripts/validate.py** - Data validation script
- Checks data quality
- Reports issues
## Configuration
The scripts use these environment variables:
- `OUTPUT_DIR` - Where to save processed files (optional)
- `MAX_ROWS` - Maximum rows to process (optional)
Set them using:
```
Set OUTPUT_DIR to /path/to/output
```
## Reference Documentation
For detailed information:
- [Data Formats](references/formats.md) - Supported data formats and schemas
- [Examples](references/examples.md) - Common usage examples
## Troubleshooting
**"File not found" error:**
- Ensure the CSV file exists
- Provide the full path to the file
**"Invalid data" error:**
- Check the CSV format matches expected schema
- See [Data Formats](references/formats.md) for requirements