c54c569f30
Completed clean root directory structure: - Root now contains only: .git, .env, docs/, orig/ - Moved all remaining files and directories to orig/: - Config files (.claude, .dockerignore, .drone.yml, etc.) - All .env variants (except active .env) - Git config (.gitconfig, .github, .gitignore, etc.) - Tool configs (.golangci.yml, .revive.toml, etc.) - Documentation (*.md files, @prompts) - Build files (Dockerfiles, Makefile, go.mod, go.sum) - Docker compose files - All source directories (scripts, tests, tools, etc.) - Runtime directories (logs, monitoring, reports) - Dependency files (node_modules, lib, cache) - Special files (--delete) - Removed empty runtime directories (bin/, data/) V2 structure is now clean: - docs/planning/ - V2 planning documents - orig/ - Complete V1 codebase preserved - .env - Active environment config (not in git) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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1.1 KiB
Uniswap V3 Pricing Function Implementation
Implement the following Uniswap V3 pricing function with high precision: $ARGUMENTS
Requirements:
- Use
github.com/holiman/uint256for all uint256 arithmetic - Ensure mathematical precision and numerical stability
- Handle edge cases and boundary conditions
- Include comprehensive test coverage
- Provide performance benchmarks
Implementation Guidelines:
- Follow the official Uniswap V3 whitepaper specifications
- Implement proper error handling for invalid inputs
- Document mathematical formulas and implementation decisions
- Optimize for performance while maintaining precision
- Consider caching strategies for expensive computations (Reference: SqrtPriceX96ToPriceCached achieved 24% performance improvement)
Optimization Techniques (Based on Successful Implementations):
- Precompute expensive constants (e.g.,
2^96,2^192) to reduce computation time - Minimize memory allocations in hot paths
- Consider object pooling for frequently created mathematical objects
- Use benchmarks to validate performance improvements