workflow:
  id: multi-agent-system
  name: Research-Driven Multi-Agent System Development
  description: Streamlined workflow for designing and implementing multi-agent AI systems using research-driven approaches.
  type: multi-agent
  project_types:
    - collaborative-agents
    - hierarchical-systems
    - specialized-agent-teams
    - distributed-intelligence
    - agent-marketplace
    - autonomous-workflows
  approach: Research multi-agent patterns and implement based on current best practices and coordination frameworks
  key_phases:
    design:
      description: Research and design multi-agent architecture
      agent: llm-architect
      actions:
        - Research current multi-agent system patterns and architectures
        - Investigate coordination and communication frameworks
        - Design system architecture based on researched approaches
        - Plan agent roles and interaction patterns
    develop:
      description: Implement agents and coordination systems
      agents: [llm-engineer, llm-architect]
      actions:
        - Research development frameworks for multi-agent systems
        - Implement individual agents using research-backed techniques
        - Develop coordination and communication mechanisms
        - Apply testing strategies for distributed systems
    orchestrate:
      description: Deploy and coordinate agent interactions
      agent: llm-engineer
      actions:
        - Research orchestration patterns and deploy coordination systems
        - Implement monitoring and observability for multi-agent interactions
        - Validate system performance and agent coordination
        - Establish maintenance and scaling procedures