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Daa Agent

Create and adapt Dynamic Agentic Architecture agents that learn and evolve

majiayu000 7cf5529 2 files · 2.0 KB Updated 567 repo stars
AI & ML

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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

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npx skillmds add majiayu000/daa-agent