Task Distribution

Task Distribution

Understanding how Agentwise allocates work among specialized agents for optimal performance.

Overview

Task distribution is the core orchestration mechanism in Agentwise that intelligently assigns work to the most appropriate agents. This system ensures maximum efficiency, parallel execution, and optimal resource utilization.

Distribution Architecture

Orchestrator Engine

The central orchestrator analyzes incoming requests and makes intelligent decisions about task allocation:

User Request → Analysis → Task Decomposition → Agent Assignment → Execution → Integration

Core Components

1. Task Analyzer: Breaks down complex requests into manageable tasks
2. Agent Matcher: Identifies the best agents for each task
3. Load Balancer: Distributes work based on agent availability
4. Dependency Manager: Handles task interdependencies
5. Progress Monitor: Tracks execution and handles failures

Task Analysis Process

1. Request Parsing

The orchestrator first analyzes the user request to understand:

• Project Type: Web app, API, mobile app, etc.
• Technologies: React, Node.js, PostgreSQL, etc.
• Complexity: Simple, moderate, complex
• Requirements: Features, constraints, preferences

// Example request analysis
{
  "request": "Build a full-stack e-commerce platform with React and Node.js",
  "analysis": {
    "projectType": "web-application",
    "technologies": ["react", "nodejs", "database"],
    "complexity": "high",
    "estimatedTasks": 12,
    "requiredAgents": ["frontend", "backend", "database", "testing"]
  }
}

2. Task Decomposition

Complex requests are broken down into atomic tasks:

// Task breakdown example
{
  "tasks": [
    {
      "id": "task-001",
      "type": "frontend",
      "description": "Create React project structure",
      "priority": "high",
      "dependencies": [],
      "estimated_tokens": 5000
    },
    {
      "id": "task-002",
      "type": "backend",
      "description": "Set up Express.js API server",
      "priority": "high",
      "dependencies": [],
      "estimated_tokens": 6000
    },
    {
      "id": "task-003",
      "type": "database",
      "description": "Design product and user schemas",
      "priority": "medium",
      "dependencies": ["task-002"],
      "estimated_tokens": 4000
    }
  ]
}

Agent Assignment Strategy

Capability Matching

Each agent has defined capabilities that are matched against task requirements:

// Agent capability matrix
{
  "frontend-specialist": {
    "technologies": ["react", "vue", "angular", "svelte"],
    "skills": ["ui-design", "state-management", "responsive-design"],
    "priority_tasks": ["component-creation", "styling", "routing"]
  },
  "backend-specialist": {
    "technologies": ["nodejs", "python", "go", "java"],
    "skills": ["api-design", "authentication", "data-processing"],
    "priority_tasks": ["server-setup", "endpoint-creation", "middleware"]
  }
}

Load Balancing Algorithms

Round Robin

Distributes tasks evenly across available agents:

Task 1 → Agent A
Task 2 → Agent B  
Task 3 → Agent C
Task 4 → Agent A (cycle repeats)

Weighted Assignment

Assigns tasks based on agent performance and capacity:

{
  "agents": {
    "frontend-specialist": { "weight": 0.4, "capacity": 3 },
    "backend-specialist": { "weight": 0.3, "capacity": 2 },
    "database-specialist": { "weight": 0.2, "capacity": 1 },
    "testing-specialist": { "weight": 0.1, "capacity": 1 }
  }
}

Priority-Based

High-priority tasks get precedence and faster agents:

{
  "priority_mapping": {
    "critical": ["frontend-specialist", "backend-specialist"],
    "high": ["database-specialist", "devops-specialist"],
    "medium": ["testing-specialist", "research-agent"],
    "low": ["documentation-agent"]
  }
}

Dependency Management

Task Dependencies

Tasks often depend on outputs from other tasks:

// Dependency graph
{
  "dependencies": {
    "frontend-components": ["api-endpoints", "data-schemas"],
    "api-endpoints": ["database-schema"],
    "testing-suite": ["frontend-components", "api-endpoints"],
    "deployment": ["testing-suite"]
  }
}

Dependency Resolution

The orchestrator creates an execution plan that respects dependencies:

Phase 1: [database-schema] → database-specialist
Phase 2: [api-endpoints] → backend-specialist  
Phase 3: [frontend-components, testing-basic] → frontend-specialist, testing-specialist
Phase 4: [integration-tests] → testing-specialist
Phase 5: [deployment] → devops-specialist

Parallel Execution Optimization

Tasks without dependencies can run in parallel:

// Parallel execution groups
{
  "parallel_groups": [
    {
      "group": 1,
      "tasks": ["database-schema", "project-setup", "design-system"],
      "agents": ["database", "devops", "frontend"]
    },
    {
      "group": 2,
      "tasks": ["api-endpoints", "ui-components"],
      "agents": ["backend", "frontend"],
      "depends_on": [1]
    }
  ]
}

Real-Time Distribution

Dynamic Assignment

The system can reassign tasks based on real-time conditions:

• Agent Availability: Reassign if agent becomes unavailable
• Performance: Move tasks to faster agents
• Workload: Balance load as new tasks arrive
• Failures: Retry with different agents

// Dynamic reassignment example
{
  "event": "agent_unavailable",
  "agent": "frontend-specialist",
  "action": "reassign",
  "tasks": ["task-005", "task-007"],
  "new_agent": "frontend-specialist-2",
  "reason": "load_balancing"
}

Queue Management

Each agent maintains a task queue with priority handling:

// Agent queue structure
{
  "agent": "backend-specialist",
  "queue": [
    {
      "task_id": "task-002",
      "priority": "high",
      "estimated_time": "5m",
      "position": 1
    },
    {
      "task_id": "task-008",
      "priority": "medium", 
      "estimated_time": "3m",
      "position": 2
    }
  ],
  "current_task": "task-001",
  "capacity": 2
}

Distribution Strategies

Project Type Strategies

Different project types use optimized distribution patterns:

Full-Stack Web Application

{
  "strategy": "full-stack-web",
  "phases": [
    {
      "name": "foundation",
      "agents": ["database", "backend"],
      "parallel": true
    },
    {
      "name": "development",
      "agents": ["frontend", "backend", "database"],
      "parallel": true
    },
    {
      "name": "integration",
      "agents": ["testing", "devops"],
      "parallel": false
    }
  ]
}

API Service

{
  "strategy": "api-service",
  "phases": [
    {
      "name": "design",
      "agents": ["backend", "database"],
      "parallel": true
    },
    {
      "name": "implementation",
      "agents": ["backend"],
      "parallel": false
    },
    {
      "name": "testing",
      "agents": ["testing"],
      "parallel": false
    }
  ]
}

Mobile Application

{
  "strategy": "mobile-app",
  "phases": [
    {
      "name": "setup",
      "agents": ["mobile", "backend"],
      "parallel": true
    },
    {
      "name": "development",
      "agents": ["mobile", "backend", "database"],
      "parallel": true
    },
    {
      "name": "testing",
      "agents": ["testing"],
      "parallel": false
    }
  ]
}

Context Sharing

Shared Context Pool

Agents share a common context to avoid redundant work:

{
  "shared_context": {
    "project_config": {
      "name": "ecommerce-app",
      "tech_stack": ["react", "nodejs", "postgresql"],
      "requirements": ["authentication", "payments", "inventory"]
    },
    "decisions": {
      "styling": "tailwindcss",
      "state_management": "zustand",
      "testing": "jest"
    },
    "progress": {
      "completed_tasks": ["task-001", "task-002"],
      "current_phase": "development"
    }
  }
}

Context Updates

Agents update shared context as they complete tasks:

// Context update from frontend agent
{
  "agent": "frontend-specialist",
  "update": {
    "components_created": ["Header", "ProductCard", "ShoppingCart"],
    "routes_defined": ["/", "/products", "/cart", "/checkout"],
    "api_integration_points": [
      { "endpoint": "/api/products", "method": "GET" },
      { "endpoint": "/api/cart", "method": "POST" }
    ]
  }
}

Performance Optimization

Token Budget Distribution

Token budgets are allocated across agents based on task complexity:

{
  "token_budget": 100000,
  "distribution": {
    "frontend-specialist": 30000,
    "backend-specialist": 25000,
    "database-specialist": 15000,
    "testing-specialist": 15000,
    "devops-specialist": 10000,
    "research-agent": 5000
  }
}

Adaptive Scheduling

The system learns from past executions to optimize future distributions:

{
  "learning_metrics": {
    "task_completion_times": {
      "frontend-component": { "avg": "3m", "std": "1m" },
      "api-endpoint": { "avg": "4m", "std": "1.5m" },
      "database-schema": { "avg": "5m", "std": "2m" }
    },
    "agent_performance": {
      "frontend-specialist": { "success_rate": 0.96, "avg_quality": 9.2 },
      "backend-specialist": { "success_rate": 0.94, "avg_quality": 8.8 }
    }
  }
}

Monitoring and Analytics

Real-Time Metrics

Track distribution performance in real-time:

{
  "current_metrics": {
    "active_agents": 3,
    "queued_tasks": 5,
    "completed_tasks": 12,
    "average_task_time": "4.2m",
    "token_usage": {
      "used": 45000,
      "remaining": 55000,
      "efficiency": 0.89
    }
  }
}

Distribution Analytics

{
  "analytics": {
    "task_distribution": {
      "frontend": 35,
      "backend": 30,
      "database": 15,
      "testing": 12,
      "devops": 8
    },
    "parallel_efficiency": 0.78,
    "dependency_bottlenecks": ["database-schema", "api-design"],
    "agent_utilization": {
      "frontend-specialist": 0.85,
      "backend-specialist": 0.92,
      "database-specialist": 0.67
    }
  }
}

Error Handling and Recovery

Task Failure Management

When tasks fail, the system implements recovery strategies:

{
  "failure_handling": {
    "retry_strategy": "exponential_backoff",
    "max_retries": 3,
    "alternative_agents": true,
    "fallback_modes": ["simplified", "manual_intervention"]
  }
}

Agent Recovery

If an agent becomes unresponsive:

1. Detection: Monitor agent health and response times
2. Isolation: Remove agent from active pool
3. Redistribution: Reassign pending tasks
4. Recovery: Attempt to restart agent
5. Fallback: Use backup agents if available

Configuration Options

Distribution Settings

{
  "distribution": {
    "strategy": "adaptive",
    "max_concurrent_agents": 5,
    "task_timeout": 300,
    "retry_attempts": 2,
    "load_balancing": "weighted",
    "priority_boost": true,
    "context_sharing": true
  }
}

Custom Distribution Rules

{
  "custom_rules": [
    {
      "condition": "task_type == 'security'",
      "action": "assign_to_security_specialist",
      "priority": "critical"
    },
    {
      "condition": "project_size > 'large'", 
      "action": "increase_agent_pool",
      "params": { "max_agents": 8 }
    },
    {
      "condition": "token_usage > 0.8",
      "action": "optimize_tasks",
      "params": { "compression": true }
    }
  ]
}

Best Practices

Optimal Distribution

1. Clear Requirements: Provide detailed project specifications
2. Appropriate Sizing: Match agent pool to project complexity
3. Dependency Planning: Design tasks to minimize bottlenecks
4. Monitor Progress: Use real-time dashboard
5. Adjust Dynamically: Respond to performance metrics

Common Patterns

Waterfall Distribution

Sequential phases with clear handoffs:

Database Design → API Development → Frontend → Testing → Deployment

Parallel Development

Independent workstreams:

Frontend ∥ Backend ∥ Database ∥ Testing

Iterative Cycles

Repeating development cycles:

Cycle 1: [Design → Develop → Test]
Cycle 2: [Design → Develop → Test]  
Cycle 3: [Design → Develop → Test]

Troubleshooting Distribution

Common Issues

1. Agent Bottlenecks: Some agents overloaded while others idle
2. Dependency Deadlocks: Circular dependencies preventing progress
3. Resource Exhaustion: Running out of tokens or time
4. Communication Failures: Agents not sharing context properly

Diagnostic Commands

# View current task distribution
npm run distribution:status

# Analyze bottlenecks
npm run distribution:analyze

# Rebalance agent workload
npm run distribution:rebalance

# Force task reassignment
npm run task:reassign <task-id> <new-agent>

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For more information, see Agent System, Performance Tuning, or Configuration.