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Add comprehensive error handling to [function_name]:
1. Identify all possible failure points
2. Add specific exception types
3. Include helpful error messages
4. Add logging at appropriate levels
5. Create fallback behavior
6. Add retry logic for transient errors
Add Type Hints
Add type hints to [file_name]:
1. Function parameters and returns
2. Class attributes
3. Use typing imports (Optional, List, Dict)
4. Add mypy-compatible annotations
5. Fix any revealed type errors
6. Maintain Python 3.10+ compatibility
Add Documentation
Add documentation to [file_name]:
1. Module docstring (purpose, usage)
2. Class docstrings
3. Method docstrings (Args, Returns, Raises)
4. Inline comments for complex logic
5. README section if needed
6. Example usage code
Refactor for Clarity
Refactor [function_name] for better readability:
1. Extract magic numbers to constants
2. Rename unclear variables
3. Break up long functions (max 20 lines)
4. Add early returns
5. Use list/dict comprehensions
6. Maintain exact behavior
Optimize Performance
Optimize [function_name]:
1. Profile current performance
2. Identify bottlenecks
3. Implement algorithm improvements
4. Add caching if applicable
5. Reduce memory allocations
6. Verify with benchmarks
Testing Prompts
Create Unit Test
Create unit tests for [class/function]:
1. Test normal operation
2. Test edge cases
3. Test error conditions
4. Use pytest
5. Mock dependencies
6. Aim for >80% coverage
Debug Issue
Debug this error: [error_message]
1. Analyze stack trace
2. Identify root cause
3. Create minimal reproduction
4. Implement fix
5. Add regression test
6. Verify fix works