ai-agent-development

AI Agent Development Workflow Overview Specialized workflow for building AI agents including single autonomous agents, multi-agent systems, agent orchestration, tool integration, and human-in-the-loop patterns. When to Use This Workflow Use this workflow when: Building autonomous AI agents Creating multi-agent systems Implementing agent orchestration Adding tool integration to agents Setting up agent memory Workflow Phases Phase 1: Agent Design Skills to Invoke ai-agents-architect - Agent architecture autonomous-agents - Autonomous patterns Actions Define agent purpose Design agent capabilities Plan tool integration Design memory system Define success metrics Copy-Paste Prompts Use @ai-agents-architect to design AI agent architecture Phase 2: Single Agent Implementation Skills to Invoke autonomous-agent-patterns - Agent patterns autonomous-agents - Autonomous agents Actions Choose agent framework Implement agent logic Add tool integration Configure memory Test agent behavior Copy-Paste Prompts Use @autonomous-agent-patterns to implement single agent Phase 3: Multi-Agent System Skills to Invoke crewai - CrewAI framework multi-agent-patterns - Multi-agent patterns Actions Define agent roles Set up agent communication Configure orchestration Implement task delegation Test coordination Copy-Paste Prompts Use @crewai to build multi-agent system with roles Phase 4: Agent Orchestration Skills to Invoke langgraph - LangGraph orchestration workflow-orchestration-patterns - Orchestration Actions Design workflow graph Implement state management Add conditional branches Configure persistence Test workflows Copy-Paste Prompts Use @langgraph to create stateful agent workflows Phase 5: Tool Integration Skills to Invoke agent-tool-builder - Tool building tool-design - Tool design Actions Identify tool needs Design tool interfaces Implement tools Add error handling Test tool usage Copy-Paste Prompts Use @agent-tool-builder to create agent tools Phase 6: Memory Systems Skills to Invoke agent-memory-systems - Memory architecture conversation-memory - Conversation memory Actions Design memory structure Implement short-term memory Set up long-term memory Add entity memory Test memory retrieval Copy-Paste Prompts Use @agent-memory-systems to implement agent memory Phase 7: Evaluation Skills to Invoke agent-evaluation - Agent evaluation evaluation - AI evaluation Actions Define evaluation criteria Create test scenarios Measure agent performance Test edge cases Iterate improvements Copy-Paste Prompts Use @agent-evaluation to evaluate agent performance Agent Architecture User Input -> Planner -> Agent -> Tools -> Memory -> Response | | | | Decompose LLM Core Actions Short/Long-term Quality Gates Agent logic working Tools integrated Memory functional Orchestration tested Evaluation passing Related Workflow Bundles ai-ml - AI/ML development rag-implementation - RAG systems workflow-automation - Workflow patterns