Core Features
SkinFlow provides a comprehensive set of features for building intelligent multi-agent applications. This guide explores the core capabilities that make SkinFlow powerful and flexible.
🧠 Multi-Agent System
Planning Agent
The Planning Agent automatically decomposes complex tasks into manageable subtasks:
// The Planning Agent analyzes requests and creates execution plans
const result = await framework.processRequest(
"Create a comprehensive e-commerce website with user authentication",
{ userId: 'user123' }
)
// The agent will:
// 1. Analyze the requirements
// 2. Break down into subtasks (database design, frontend, backend, etc.)
// 3. Assign appropriate agents to each subtask
// 4. Coordinate the executionSpecialized Sub-Agents
SkinFlow includes specialized agents for different domains:
- Research Agent: Gather information and conduct analysis
- Programming Agent: Write, review, and debug code
- Data Analysis Agent: Process and analyze data
- Content Creation Agent: Generate written content and media
- Design Agent: Create UI/UX designs and graphics
Agent Coordination
Agents work together through a sophisticated coordination system:
// Agents can collaborate on complex tasks
const collaboration = await framework.processRequest(
"Research market trends and create a business plan with financial projections",
{ userId: 'user123' }
)
// Multiple agents will work together:
// - Research Agent: Gather market data
// - Data Analysis Agent: Analyze trends
// - Content Creation Agent: Write business plan
// - Programming Agent: Create financial models💾 Advanced Memory System
Short-term Memory
Maintains context during active sessions:
// Configure short-term memory
const framework = await createMultiAgentFramework({
memory: {
storage: {
type: 'memory'
},
maxShortTermMemory: 100, // Maximum context items
contextWindow: 4000 // Context token limit
}
})Long-term Memory
Persistent storage for knowledge and history:
// PostgreSQL-based long-term memory
const framework = await createMultiAgentFramework({
memory: {
storage: {
type: 'postgres',
config: {
host: 'localhost',
database: 'skingflow',
user: 'postgres',
password: 'your-password'
}
},
// Memory retention settings
maxLongTermMemory: 10000,
memoryTTL: 30 * 24 * 60 * 60 * 1000 // 30 days
}
})Semantic Search
Vector-based intelligent memory retrieval:
// Agents can search through past interactions
const relevantMemories = await framework.memory.search(
"user preferences for dark theme",
{ userId: 'user123', limit: 5 }
)User Preferences
Learns and adapts to user preferences:
// Preferences are automatically learned and stored
await framework.processRequest(
"I prefer concise responses with bullet points",
{ userId: 'user123' }
)
// Future responses will adapt to this preference🛠️ Unified Tool System
Built-in Tools
SkinFlow includes a comprehensive set of built-in tools:
// File system operations
await framework.processRequest(
"Create a backup of the project directory",
{ userId: 'user123' }
)
// Web operations
await framework.processRequest(
"Research the latest AI trends and summarize findings",
{ userId: 'user123' }
)
// Data processing
await framework.processRequest(
"Analyze the sales data and create a visualization",
{ userId: 'user123' }
)Custom Tools
Extend functionality with custom tools:
// Define custom tools
const customTools = [
{
name: 'send_email',
description: 'Send an email using SMTP',
parameters: {
type: 'object',
properties: {
to: { type: 'string', description: 'Recipient email' },
subject: { type: 'string', description: 'Email subject' },
body: { type: 'string', description: 'Email body' }
},
required: ['to', 'subject', 'body']
},
handler: async (params) => {
// Your email sending implementation
return { success: true, message: 'Email sent successfully' }
}
}
]
const framework = await createMultiAgentFramework({
tools: { customTools }
})Tool Security
Secure tool execution with permission control:
// Configure tool permissions
const framework = await createMultiAgentFramework({
tools: {
security: {
enableSandbox: true,
allowedOperations: ['read', 'write'],
restrictedPaths: ['/etc', '/system']
}
}
})🔄 Stream Processing Engine
Real-time Processing
Process requests with streaming output:
// Stream responses in real-time
const stream = await framework.processRequestStream(
"Write a detailed analysis of current AI trends",
{ userId: 'user123' }
)
for await (const chunk of stream) {
console.log(chunk.content) // Real-time output
}Asynchronous Execution
Run multiple tasks concurrently:
// Execute multiple requests in parallel
const results = await Promise.all([
framework.processRequest("Task 1", { userId: 'user123' }),
framework.processRequest("Task 2", { userId: 'user123' }),
framework.processRequest("Task 3", { userId: 'user123' })
])Workflow Orchestration
Complex workflow management:
// Define complex workflows
const workflow = {
steps: [
{
name: 'research',
agent: 'research',
input: 'Gather market data'
},
{
name: 'analysis',
agent: 'data-analysis',
input: 'Analyze the research data'
},
{
name: 'report',
agent: 'content-creation',
input: 'Create comprehensive report'
}
]
}
const result = await framework.executeWorkflow(workflow, { userId: 'user123' })🛡️ Enterprise-Grade Reliability
Error Recovery
Multi-layer error handling and recovery:
// Automatic retry and fallback mechanisms
const framework = await createMultiAgentFramework({
fallback: {
enableRetry: true,
maxRetries: 3,
retryDelay: 1000,
fallbackModels: ['gpt-3.5-turbo', 'claude-instant']
}
})Circuit Breaker
Prevent cascading failures:
// Circuit breaker configuration
const framework = await createMultiAgentFramework({
circuitBreaker: {
enable: true,
failureThreshold: 5,
recoveryTimeout: 60000,
expectedException: ['LLM_API_ERROR', 'TIMEOUT_ERROR']
}
})Health Monitoring
Real-time system health tracking:
// Monitor system health
const health = await framework.getHealthStatus()
console.log('System Health:', health)
// Output:
// {
// status: 'healthy',
// llm: 'connected',
// memory: 'connected',
// agents: 'available',
// tools: 'operational'
// }Comprehensive Logging
Detailed logging and debugging:
// Configure logging
const framework = await createMultiAgentFramework({
logging: {
level: 'debug',
enableMetrics: true,
logToFile: true,
logFormat: 'json'
}
})🔌 Extensibility
Plugin System
Extend functionality with plugins:
// Custom plugin
const analyticsPlugin = {
name: 'analytics',
hooks: {
beforeRequest: (request) => {
console.log('Processing request:', request.type)
},
afterResponse: (response) => {
console.log('Request completed:', response.success)
}
}
}
const framework = await createMultiAgentFramework({
plugins: [analyticsPlugin]
})Middleware
Add custom processing logic:
// Request middleware
const framework = await createMultiAgentFramework({
middleware: [
{
name: 'auth',
process: async (request, next) => {
// Custom authentication logic
if (!request.userId) {
throw new Error('User ID required')
}
return await next(request)
}
}
]
})🎯 Performance Optimization
Caching
Intelligent caching for improved performance:
// Configure caching
const framework = await createMultiAgentFramework({
cache: {
enable: true,
ttl: 300000, // 5 minutes
maxSize: 1000,
strategy: 'lru'
}
})Resource Management
Optimize resource usage:
// Resource management
const framework = await createMultiAgentFramework({
resources: {
maxConcurrentRequests: 10,
maxMemoryUsage: '512MB',
timeout: 30000
}
})Next Steps
- Architecture - Understand the system design
- Configuration - Learn about configuration options
- API Reference - Detailed API documentation
- Examples - Practical implementations