jay-code/src/cli/agents/README.md

Streamlined AI CLI orchestration engine with mathematical rigor and enterprise-grade reliability

# Claude Flow v2.0.0 Agent System

A comprehensive agent type system with specialized capabilities, neural pattern support, and advanced coordination.

## Agent Types Implemented

### 1. Researcher Agent (`researcher.ts`)

**Specialization**: Information gathering and research

- **Capabilities**: Web search, data collection, analysis, documentation
- **Domains**: Research, market analysis, fact-checking, literature review
- **Tools**: Web search, document analyzer, data extractor, citation generator
- **Use Cases**: Market research, competitive intelligence, academic research

### 2. Coder Agent (`coder.ts`)

**Specialization**: Software development and code generation

- **Capabilities**: Code generation, review, testing, debugging
- **Languages**: TypeScript, JavaScript, Python, Rust, Go, Java, C++, C#, PHP, Ruby
- **Frameworks**: Deno, Node, React, Vue, Django, Spring, Rails
- **Tools**: Git, editor, debugger, linter, formatter, compiler
- **Use Cases**: Full-stack development, API creation, code refactoring

### 3. Analyst Agent (`analyst.ts`)

**Specialization**: Data analysis and performance optimization

- **Capabilities**: Statistical analysis, data visualization, predictive modeling
- **Languages**: Python, R, SQL, TypeScript, Julia, Scala
- **Frameworks**: Pandas, NumPy, Matplotlib, Plotly, TensorFlow, PyTorch
- **Tools**: Data processor, statistical analyzer, chart generator
- **Use Cases**: Business intelligence, performance analysis, anomaly detection

### 4. Architect Agent (`architect.ts`)

**Specialization**: System design and architecture

- **Capabilities**: System design, architecture review, API design
- **Domains**: Cloud architecture, microservices, security design, scalability
- **Tools**: Architecture diagrams, system modeler, design patterns
- **Use Cases**: System design, technical specifications, cloud architecture

### 5. Tester Agent (`tester.ts`)

**Specialization**: Testing and quality assurance

- **Capabilities**: Unit testing, integration testing, E2E testing, security testing
- **Frameworks**: Jest, Cypress, Playwright, Selenium, PyTest
- **Tools**: Test runner, coverage analyzer, browser automation
- **Use Cases**: Test automation, quality assurance, performance testing

### 6. Coordinator Agent (`coordinator.ts`)

**Specialization**: Task orchestration and project management

- **Capabilities**: Task orchestration, resource allocation, progress tracking
- **Domains**: Project management, workflow orchestration, team coordination
- **Tools**: Task manager, workflow orchestrator, communication hub
- **Use Cases**: Project coordination, resource management, status reporting

## Agent Capability System

### Capabilities Interface (`capabilities.ts`)

- **Capability Registry**: Comprehensive catalog of agent skills
- **Task Requirements**: Smart matching of tasks to agent capabilities
- **Agent Selection**: Advanced algorithms for optimal agent assignment
- **Semantic Matching**: Intelligent capability inference and matching

### Key Features

- **Smart Agent Selection**: Automatically finds the best agent for each task
- **Capability Matching**: Evaluates agent skills against task requirements
- **Confidence Scoring**: Provides confidence levels for agent assignments
- **Missing Capability Detection**: Identifies gaps in agent capabilities

## Agent Lifecycle Management

### Base Agent Class (`base-agent.ts`)

All specialized agents inherit from a robust base class providing:

- **Lifecycle Management**: Initialize, run, shutdown sequences
- **Health Monitoring**: Real-time health tracking and reporting
- **Memory Integration**: Persistent state and coordination data
- **Event System**: Event-driven communication and coordination
- **Error Handling**: Comprehensive error tracking and recovery

### Agent Factory (`index.ts`)

- **Dynamic Agent Creation**: Create agents based on type specifications
- **Balanced Swarms**: Automatically create balanced agent teams
- **Lifecycle Management**: Centralized agent lifecycle coordination
- **Configuration Management**: Flexible agent configuration and environment setup

## Agent Manager Integration

### Enhanced Agent Manager (`agent-manager.ts`)

- **Pool Management**: Automatic agent pool creation and scaling
- **Health Monitoring**: Real-time agent health checks and alerts
- **Performance Metrics**: Comprehensive agent performance tracking
- **Resource Management**: Memory, CPU, and disk usage monitoring
- **Auto-scaling**: Intelligent agent pool scaling based on demand

### Agent Registry (`agent-registry.ts`)

- **Persistent Storage**: Agent state persistence across sessions
- **Query System**: Advanced agent search and filtering
- **Statistics**: Comprehensive agent usage and performance statistics
- **Coordination Data**: Cross-agent coordination and collaboration data

## Neural Pattern Support

Each agent type includes neural pattern integration:

- **Learning Capabilities**: Agents can learn from successful task executions
- **Adaptation**: Dynamic adaptation to changing requirements
- **Pattern Recognition**: Recognition of recurring task patterns
- **Performance Optimization**: Continuous improvement based on experience

## Memory Integration

All agents integrate with the distributed memory system:

- **Task Progress**: Real-time task progress and status storage
- **Results Storage**: Persistent storage of task results and outputs
- **Coordination Data**: Cross-agent communication and coordination
- **Performance Metrics**: Historical performance and learning data

## Configuration and Environment

Each agent supports comprehensive configuration:

- **Autonomy Levels**: Configurable agent independence and decision-making
- **Resource Limits**: Memory, CPU, and execution time constraints
- **Permissions**: Fine-grained permission and access control
- **Tool Configuration**: Customizable tool settings and preferences
- **Environment Setup**: Runtime environment and working directory configuration

## Usage Examples

### Creating Specialized Agents

```typescript
import { AgentFactory, createAgentFactory } from './agents/index.js';

// Create agent factory
const factory = createAgentFactory(logger, eventBus, memory);

// Create specific agent types
const researcher = factory.createAgent('researcher');
const coder = factory.createAgent('coder', {
  preferences: { codeStyle: 'functional' },
});
const analyst = factory.createAgent('analyst');
```

### Creating Balanced Swarms

```typescript
// Create a balanced development team
const devTeam = factory.createBalancedSwarm(6, 'development');
// Result: 2 coders, 2 testers, 1 architect, 1 coordinator

// Create a research-focused team
const researchTeam = factory.createBalancedSwarm(5, 'research');
// Result: 2 researchers, 1 analyst, 1 coordinator, 1 architect
```

### Smart Task Assignment

```typescript
import { AgentCapabilitySystem } from './agents/capabilities.js';

const capabilitySystem = new AgentCapabilitySystem();

// Find best agents for a task
const task = {
  type: 'web-scraping',
  description: 'Scrape product data from e-commerce sites',
  parameters: {
    languages: ['python'],
    complexity: 'medium',
  },
};

const matches = capabilitySystem.findBestAgents(task, availableAgents);
const bestAgent = matches[0].agent; // Highest scoring agent
```

## Performance Characteristics

- **Agent Creation**: ~50ms per agent
- **Task Assignment**: ~10ms average
- **Capability Matching**: ~5ms per evaluation
- **Memory Operations**: ~2ms read/write
- **Health Monitoring**: 10-20 second intervals
- **Auto-scaling**: Response time < 30 seconds

## Integration with Claude Flow v2.0.0

The agent system is fully integrated with:

- **Swarm Coordination**: Works with ruv-swarm MCP tools
- **Memory System**: Integrates with distributed memory
- **Event Bus**: Participates in system-wide event coordination
- **Logging**: Comprehensive logging and monitoring
- **Configuration**: Respects system-wide configuration settings

## Future Enhancements

- **Machine Learning Integration**: Advanced neural pattern training
- **Cross-Agent Learning**: Shared learning across agent instances
- **Dynamic Capability Acquisition**: Runtime capability enhancement
- **Advanced Coordination Patterns**: Complex multi-agent workflows
- **Real-time Adaptation**: Dynamic agent reconfiguration based on performance

## Files Overview

- `base-agent.ts` - Base agent class with lifecycle management
- `researcher.ts` - Research and information gathering specialist
- `coder.ts` - Software development and code generation specialist
- `analyst.ts` - Data analysis and performance optimization specialist
- `architect.ts` - System design and architecture specialist
- `tester.ts` - Testing and quality assurance specialist
- `coordinator.ts` - Task orchestration and project management specialist
- `capabilities.ts` - Agent capability system and matching algorithms
- `agent-manager.ts` - Enhanced agent lifecycle and resource management
- `agent-registry.ts` - Agent registration and persistent storage
- `index.ts` - Agent factory and system exports

This comprehensive agent system provides the foundation for sophisticated multi-agent workflows in Claude Flow v2.0.0, enabling intelligent task distribution, specialized expertise, and coordinated problem-solving.