klingai-known-pitfalls

# Klingai Known Pitfalls

## Overview

This skill documents common mistakes, gotchas, and pitfalls when working with Kling AI, along with solutions and best practices to avoid them.

## Prerequisites

- Basic Kling AI usage experience
- Encountered issues to troubleshoot
- Desire to improve implementation

## Instructions

Follow these steps to avoid pitfalls:

1. **Review Common Issues**: Understand frequent problems
2. **Apply Best Practices**: Implement recommendations
3. **Test Thoroughly**: Validate implementations
4. **Monitor Continuously**: Watch for new issues
5. **Update Regularly**: Keep up with API changes

## Output

Successful execution produces:
- Robust error handling
- Proper async patterns
- Secure credential management
- Cost-controlled generation

## Error Handling

See `{baseDir}/references/errors.md` for comprehensive error handling.

## Examples

See `{baseDir}/references/examples.md` for detailed examples.

## Resources

- [Kling AI Best Practices](https://docs.klingai.com/best-practices)
- [API Error Reference](https://docs.klingai.com/errors)
- [Security Guidelines](https://docs.klingai.com/security)