chore(ai): add comprehensive CLI configurations for all AI assistants
Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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.qwen/config/optimization.md
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.qwen/config/optimization.md
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# Qwen Code Performance Optimization Settings
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## Workflow Preferences
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- **Always commit changes**: Use `git commit -am "math: descriptive message"` for mathematical implementations
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- **Branch naming**: Use prefixes (`math-sqrt-price`, `algo-liquidity-calc`, `perf-uniswap`)
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- **Context management**: Focus on mathematical precision and performance
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- **Parallel processing**: Leverage Go's concurrency patterns for independent calculations
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## File Organization Preferences
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- **Mathematical functions**: Place in `pkg/uniswap/` or `pkg/math/`
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- **Test files**: Place alongside source files with `_test.go` suffix
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- **Documentation**: Inline comments explaining mathematical formulas
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- **Precision libraries**: Use `github.com/holiman/uint256` for uint256 arithmetic
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## Performance Monitoring
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```bash
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# Enable metrics endpoint for performance tracking
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export METRICS_ENABLED="true"
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export METRICS_PORT="9090"
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# Monitor memory usage of mathematical calculations
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go tool pprof http://localhost:9090/debug/pprof/heap
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# Monitor CPU usage of mathematical functions
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go tool pprof http://localhost:9090/debug/pprof/profile?seconds=30
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# Run benchmarks for mathematical functions
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go test -bench=. -benchmem ./pkg/uniswap/...
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```
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## Precision Requirements
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- **Uint256 Arithmetic**: Use `github.com/holiman/uint256` for all uint256 calculations
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- **Floating Point**: Use `math/big` for floating-point calculations when needed
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- **Rounding**: Implement proper rounding strategies for financial calculations
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- **Overflow Handling**: Handle overflow and underflow conditions properly
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## Optimization Focus Areas
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1. **Mathematical Computation Efficiency**
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- Minimize computational overhead in pricing functions
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- Optimize sqrtPriceX96 to price conversions
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- Efficient tick calculations
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2. **Memory Allocation Reduction**
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- Object pooling for frequently created mathematical objects
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- Pre-allocation of slices and buffers
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- Minimize garbage collection pressure
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3. **Algorithmic Optimization**
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- Mathematical formula simplification
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- Lookup table implementation for repeated calculations
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- Caching strategies for expensive computations
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