Awesome-omni-skill project-overview
Background knowledge about CaCrFeedFormula project architecture, features, and context. Automatically loaded for AI reference, not directly user-invocable.
git clone https://github.com/diegosouzapw/awesome-omni-skill
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/development/project-overview-majiayu000" ~/.claude/skills/diegosouzapw-awesome-omni-skill-project-overview-024c38 && rm -rf "$T"
skills/development/project-overview-majiayu000/SKILL.mdCaCrFeedFormula Project Overview
Intelligent Feed Formula Optimization System built with Tauri + Rust + React TypeScript.
Project Context
CaCrFeedFormula is an industrial-grade desktop application for feed formula optimization, integrating AI-assisted optimization, linear programming (HiGHS solver), and comprehensive feed management capabilities.
Core Technology Stack
Backend (Rust 2021):
- Framework: Tauri 2.9.0 + Tokio 1.37 (full async runtime)
- Database: SQLite + SQLx 0.7 (compile-time type safety)
- Optimization: HiGHS 1.12 (industrial-grade LP solver)
- Caching: Moka 0.12 (high-performance concurrent cache)
- Type Binding: specta 2.0 + tauri-specta 2.0 (auto TypeScript generation)
- AI Integration: reqwest + eventsource-stream (streaming responses)
- Parallel Compute: Rayon 1.8
Frontend (React 19.1 + TypeScript 5.8):
- UI Framework: Ant Design 5.26 + Tailwind CSS 4.1
- State Management: TanStack Query 5.17
- Build Tool: Vite 7.0
- Visualization: Recharts 2.15
- Animation: Framer Motion 11
Project Structure
cacrfeedformula/ ├── src/ # Rust backend source │ ├── ai/ # AI service module │ ├── database/ # Database connection │ ├── formula/ # Formula optimization core │ ├── material/ # Material management │ ├── species/ # Species management │ ├── factory/ # Factory management │ ├── premix/ # Premix design │ ├── profit/ # Profit/loss analysis │ ├── prediction/ # Nutrition prediction │ ├── production_batch/ # Production batch management │ └── system/ # System services ├── frontend/ # React frontend source │ └── src/ │ ├── components/ # React components │ │ ├── AIChat/ # AI chat component │ │ └── common/ # Common components │ └── bindings.ts # Auto-generated type bindings ├── migrations/ # Database migrations └── .claude/ ├── skills/ # Custom Claude Code skills └── rules/ # Detailed development standards
Core Features
1. Formula Optimization System
- Linear programming optimization (cost minimization)
- Manual formula design
- Premix reverse calculation design
- Formula version management
- Formula analysis and reporting
- 167 Tauri commands for comprehensive formula operations
2. Data Management
- Material management (built-in China Feed Composition & Nutrition Value Database)
- Species management (multiple species, growth stages, nutrition standards)
- Factory management (multi-factory data isolation)
- Production batch management (batch lifecycle, material requirement calculation)
- Inventory management (stock check, variance analysis, purchase planning)
3. Analysis & Decision Support
- Profit/loss analysis (comprehensive cost accounting, real-time P&L)
- Nutrition prediction (NRC-based energy prediction)
- Sensitivity analysis (shadow prices, bottleneck constraint identification)
4. AI Intelligent Assistant
- Context-aware professional feed formula consultation
- Streaming responses with typewriter effect
- Multi-turn conversations
- Supports OpenAI, DeepSeek, OpenRouter platforms
Project Characteristics
- Desktop Application: Not a web app; cross-platform desktop app built with Tauri
- High-Performance Computing: Rust backend ensures speed and stability
- Type Safety: specta auto-generates TypeScript types, ensuring frontend-backend type consistency
- Async-First: Comprehensive use of Tokio async runtime
- Industrial-Grade Optimization: HiGHS solver supports large-scale formula optimization
- AI Integration: Streaming AI responses with real-time typewriter effect
Development Workflow Context
Typical Development Scenarios:
- Formula Engine: Implementing complex linear programming algorithms with HiGHS
- Material Database: Managing large datasets with SQLite + SQLx
- Desktop UI: Building responsive Ant Design interfaces with React 19
- Tauri Commands: Creating type-safe Rust ↔ TypeScript communication
- AI Features: Integrating streaming AI responses into desktop workflows
- Batch Processing: Handling production batch calculations and scheduling
Key Integration Points:
- Rust ↔ TypeScript: specta generates bindings.ts after every Rust change
- Database ↔ Business Logic: SQLx macros provide compile-time SQL validation
- Frontend ↔ Backend: TanStack Query manages server state via Tauri commands
- AI ↔ User: Streaming SSE responses with real-time UI updates
Project Scale
- 167 Tauri commands across 10 modules
- Comprehensive feed database with 1000+ materials
- Multi-tenancy support with factory-level data isolation
- Complex optimization handling 100+ variables and 50+ constraints
Development Standards
The project follows strict development standards documented in
.claude/rules/:
- Rust backend standards (02-rust-backend-standards.md)
- React frontend standards (03-react-frontend-standards.md)
- Database standards (04-database-standards.md)
- LSP usage standards (05-lsp-usage-standards.md)
All these standards are enforced via automated hooks and skills.
When This Context Is Useful
This project overview is automatically loaded to help Claude understand:
- Architecture decisions when proposing changes
- Technology choices when solving problems
- Integration patterns when adding features
- Scale considerations when optimizing performance
- Domain context (feed formulation, nutrition, optimization)
This knowledge enables Claude to make more informed, project-appropriate recommendations without requiring repeated explanations of the project's nature and structure.