DAA Agent

Create agents with Dynamic Agentic Architecture that adapt and learn over time.

When to use

When you need agents that go beyond static configurations — agents that adapt their behavior based on performance metrics, learn from interactions, and share knowledge with other agents.

Steps

1. Create agent — call mcp__claude-flow__daa_agent_create with initial configuration and learning parameters
2. Monitor learning — call mcp__claude-flow__daa_learning_status to see adaptation progress
3. Check performance — call mcp__claude-flow__daa_performance_metrics for efficiency and accuracy metrics
4. Adapt — call mcp__claude-flow__daa_agent_adapt to trigger manual adaptation based on feedback
5. Share knowledge — call mcp__claude-flow__daa_knowledge_share to propagate learnings to other agents

DAA vs static agents

Aspect	Static Agent	DAA Agent
Behavior	Fixed configuration	Adapts over time
Learning	None	Continuous from interactions
Knowledge	Isolated	Shared across agents
Performance	Constant	Improves with use