#!/usr/bin/env python3
"""
test.example - A simple test skill for validating the meta.create orchestrator workflow

Generated by meta.skill with Betty Framework certification
"""

import os
import sys
import json
import yaml
from pathlib import Path
from typing import Dict, List, Any, Optional


from betty.config import BASE_DIR
from betty.logging_utils import setup_logger
from betty.certification import certified_skill

logger = setup_logger(__name__)


class TestExample:
    """
    A simple test skill for validating the meta.create orchestrator workflow
    """

    def __init__(self, base_dir: str = BASE_DIR):
        """Initialize skill"""
        self.base_dir = Path(base_dir)

    @certified_skill("test.example")
    def execute(self, input_data_string___test_input_data: Optional[str] = None) -> Dict[str, Any]:
        """
        Execute the skill

        Returns:
            Dict with execution results
        """
        try:
            logger.info("Executing test.example...")

            # TODO: Implement skill logic here

            # Implementation notes:
            # This is a minimal test skill to verify that meta.create can properly orchestrate the creation of skills, check for duplicates, and validate compatibility.

            # Placeholder implementation
            result = {
                "ok": True,
                "status": "success",
                "message": "Skill executed successfully"
            }

            logger.info("Skill completed successfully")
            return result

        except Exception as e:
            logger.error(f"Error executing skill: {e}")
            return {
                "ok": False,
                "status": "failed",
                "error": str(e)
            }


def main():
    """CLI entry point"""
    import argparse

    parser = argparse.ArgumentParser(
        description="A simple test skill for validating the meta.create orchestrator workflow"
    )

    parser.add_argument(
        "--input-data-string---test-input-data",
        help="input_data (string) - Test input data"
    )
    parser.add_argument(
        "--output-format",
        choices=["json", "yaml"],
        default="json",
        help="Output format"
    )

    args = parser.parse_args()

    # Create skill instance
    skill = TestExample()

    # Execute skill
    result = skill.execute(
        input_data_string___test_input_data=args.input_data_string___test_input_data,
    )

    # Output result
    if args.output_format == "json":
        print(json.dumps(result, indent=2))
    else:
        print(yaml.dump(result, default_flow_style=False))

    # Exit with appropriate code
    sys.exit(0 if result.get("ok") else 1)


if __name__ == "__main__":
    main()