@cloudkinetix/bmad-enhanced
Version:
Cloud-Kinetix enhanced fork of BMAD-METHOD - Breakthrough Method of Agile AI-driven Development with robust versioning and unified validation.
38 lines • 1.7 kB
YAML
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