tenets

# Tenets Architecture Documentation Tenets is a sophisticated, local-first code intelligence platform that revolutionizes how developers interact with their codebases when working with AI assistants. This documentation provides a comprehensive overview of the system's architecture, organized into specialized areas. ## Overview Tenets employs advanced multi-stage analysis combining NLP, ML, static code analysis, git history mining, and intelligent ranking to build optimal context for AI interactions. The system is designed with local-first processing, progressive enhancement, intelligent caching, and configurable intelligence as core principles. ## Architecture Components ### Core System - **[System Overview](architecture/system-overview.md)** - Core philosophy and architecture principles - **[Complete System Architecture](architecture/core-architecture.md)** - High-level data flow and component diagrams - **[Performance Architecture](architecture/performance.md)** - Optimization strategies and performance considerations ### Processing Pipeline - **[NLP/ML Pipeline](architecture/nlp-pipeline.md)** - Natural language processing and machine learning components - **[File Discovery & Scanning](architecture/file-scanning.md)** - Intelligent file discovery and filtering system - **[Code Analysis Engine](architecture/code-analysis.md)** - Multi-language code analysis and AST parsing - **[Relevance Ranking System](architecture/ranking-system.md)** - Multi-factor ranking algorithms and strategies ### Intelligence & Context - **[Context Management & Optimization](architecture/context-management.md)** - Context building and token optimization - **[Git Integration & Chronicle System](architecture/git-integration.md)** - Git analysis and repository insights - **[Guiding Principles (Tenets) System](architecture/guiding-principles.md)** - Persistent instruction system ### Data & Storage - **[Session Management](architecture/session-management.md)** - Session lifecycle and state management - **[Storage & Caching Architecture](architecture/storage-caching.md)** - Multi-tier caching and persistence - **[Configuration System](architecture/configuration.md)** - Hierarchical configuration management ### Interfaces & Security - **[CLI & API Architecture](architecture/cli-api.md)** - Command-line and programmatic interfaces - **[Output Generation & Visualization](architecture/output-visualization.md)** - Report generation and visualization - **[Security & Privacy Architecture](architecture/security.md)** - Local-first security model and privacy protection ### Protocol & Integration - **[MCP Integration Plan](architecture/mcp-integration-plan.md)** - Model Context Protocol server architecture - **[Future Roadmap & Vision](architecture/roadmap.md)** - Development roadmap and long-term vision ### Quality & Future - **[Testing & Quality Assurance](architecture/testing.md)** - Testing strategies and quality metrics ## Key Features - **Local-First Processing**: All analysis happens locally, ensuring complete privacy - **Progressive Enhancement**: Works immediately with basic Python, scales with optional dependencies - **Intelligent Caching**: Multi-level caching for optimal performance - **Configurable Intelligence**: Every aspect can be tuned and customized - **Streaming Architecture**: Real-time results as analysis progresses ## Quick Start For implementation details and usage examples, refer to the individual architecture documents. Each component is designed to work independently while contributing to the overall system intelligence. ## Architecture Principles 1. **Privacy by Design**: No code leaves the local environment 2. **Performance First**: Optimized for speed and efficiency 3. **Extensibility**: Modular design for easy enhancement 4. **Developer Experience**: Intuitive interfaces and comprehensive tooling The future of code intelligence is local, intelligent, and developer-centric. Tenets embodies this vision while remaining practical and immediately useful for development teams of any size.