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CODI Architecture Specification

Vision​

CODI (CODITECT Intelligence) is the proprietary command-line interface that serves as the primary interaction point between developers, AI agents, and the CODITECT platform. It's the "magic sauce" that enables autonomous, intelligent software development.

Core Philosophy​

  1. Intelligent Monitoring - Not just tracking, but understanding development patterns
  2. Agent Orchestration - Seamless coordination between human and AI agents
  3. Quality Enforcement - Automatic enforcement of CODITECT standards
  4. Knowledge Preservation - Every action contributes to the collective intelligence

Functional Requirements​

1. Development Lifecycle Management​

Session Intelligence​

  • Automatic session initialization with environment detection
  • Multi-session coordination and conflict prevention
  • Session handoff between human and AI agents
  • Persistent session state across restarts

Monitoring & Attribution​

  • Real-time file operation tracking
  • Intelligent AI tool detection (20+ tools)
  • Actor attribution with context
  • Performance metrics collection
  • Quality metrics enforcement

2. Agent Orchestration System​

Agent Lifecycle​

  • Agent discovery and registration
  • Capability-based task routing
  • Inter-agent communication
  • Resource allocation and optimization
  • Performance tracking per agent

Task Management​

  • Task decomposition and distribution
  • Dependency resolution
  • Progress tracking with milestones
  • Automatic escalation on blockage
  • Result aggregation and reporting

3. Knowledge Management​

Context Preservation​

  • Automatic export detection and archival
  • Session transcript management
  • Code change correlation
  • Decision history tracking
  • Learning from patterns

Search & Analysis​

  • Semantic search across all artifacts
  • Pattern detection in development
  • Anomaly detection and alerting
  • Trend analysis and reporting
  • Predictive suggestions

4. Quality Assurance​

Standards Enforcement​

  • ADR compliance checking
  • Code style verification
  • Test coverage monitoring
  • Documentation requirements
  • Security scanning

Continuous Improvement​

  • Metric collection and analysis
  • Performance benchmarking
  • Best practice identification
  • Automated optimization suggestions

5. Integration Capabilities​

Platform Integration​

  • FoundationDB connection
  • Cloud Run deployment hooks
  • Git workflow automation
  • CI/CD pipeline integration
  • Monitoring system feeds

AI Integration​

  • Multi-provider support
  • Model selection optimization
  • Token usage tracking
  • Cost optimization
  • Quality/speed tradeoffs

Technical Architecture​

Component Design​

┌─────────────────────────────────────────┐
│            CODI CLI (Rust)              │
├─────────────────────────────────────────┤
│         Command Parser (Clap)           │
├─────────────────────────────────────────┤
│     Core Services Layer                 │
│  ┌─────────┬──────────┬────────────┐  │
│  │Monitor  │ Agent    │ Knowledge  │  │
│  │Service  │ Service  │ Service    │  │
│  └─────────┴──────────┴────────────┘  │
├─────────────────────────────────────────┤
│         Data Layer                      │
│  ┌─────────┬──────────┬────────────┐  │
│  │ JSON    │ FDB      │ File       │  │
│  │ Logs    │ Client   │ System     │  │
│  └─────────┴──────────┴────────────┘  │
└─────────────────────────────────────────┘

Data Models​

Session Model​

struct Session {
    id: Uuid,
    type: SessionType,
    actor: Actor,
    started: DateTime,
    status: SessionStatus,
    metadata: HashMap<String, Value>,
}

enum SessionType {
    Human,
    AITool(String),
    Agent(String),
    System,
}

Operation Model​

struct Operation {
    id: Uuid,
    session_id: Uuid,
    timestamp: DateTime,
    action: Action,
    resource: Resource,
    result: OperationResult,
    metrics: OperationMetrics,
}

Agent Model​

struct Agent {
    id: String,
    name: String,
    capabilities: Vec<Capability>,
    performance: PerformanceMetrics,
    status: AgentStatus,
}

Security & Licensing​

Licensing Strategy​

  • Proprietary License - Not MIT
  • Source Available - Visible but not freely usable
  • Commercial License - For enterprise usage
  • Attribution Required - CODITECT branding mandatory

Security Features​

  • Encrypted communication
  • Secure credential storage
  • Audit logging
  • Access control
  • Data isolation

Performance Requirements​

  • Startup time: < 100ms
  • Command execution: < 50ms overhead
  • Log search: < 500ms for 1M entries
  • Memory usage: < 50MB baseline
  • CPU usage: < 5% when monitoring

Command Taxonomy​

Primary Commands​

codi monitor    - Monitoring operations
codi agent      - Agent management
codi session    - Session management
codi know       - Knowledge operations
codi quality    - Quality enforcement
codi integrate  - Integration tools

Intelligent Features​

codi suggest    - AI-powered suggestions
codi analyze    - Pattern analysis
codi optimize   - Performance optimization
codi learn      - Learning from history

Administrative​

codi config     - Configuration management
codi license    - License management
codi telemetry  - Usage analytics
codi upgrade    - Self-update capability

Future Capabilities​

Phase 1: Foundation​

  • Core monitoring and logging
  • Basic agent management
  • Session coordination

Phase 2: Intelligence​

  • Pattern recognition
  • Predictive analytics
  • Automated suggestions

Phase 3: Autonomy​

  • Self-optimization
  • Automatic error recovery
  • Proactive problem solving

Phase 4: Ecosystem​

  • Plugin architecture
  • Third-party integrations
  • Marketplace for agents

Success Metrics​

  1. Developer Productivity: 10x improvement
  2. Quality Metrics: 99%+ compliance
  3. Agent Utilization: 80%+ efficiency
  4. Knowledge Retention: 100% capture
  5. Error Reduction: 90% decrease

Conclusion​

CODI is not just a CLI tool - it's the intelligent interface that makes CODITECT's vision of autonomous development a reality. Every feature should contribute to the goal of making software development more intelligent, efficient, and autonomous.