AgentSkillsCN

ai-agent-development

AI智能体开发工作流，用于构建自主智能体、多智能体系统以及借助CrewAI、LangGraph和自定义智能体进行智能体编排。

SKILL.md
--- frontmatter
name: ai-agent-development
description: "AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents."
source: personal
risk: safe
domain: ai-ml
category: granular-workflow-bundle
version: 1.0.0

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

  1. •Define agent purpose
  2. •Design agent capabilities
  3. •Plan tool integration
  4. •Design memory system
  5. •Define success metrics

Copy-Paste Prompts

code
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

  1. •Choose agent framework
  2. •Implement agent logic
  3. •Add tool integration
  4. •Configure memory
  5. •Test agent behavior

Copy-Paste Prompts

code
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

  1. •Define agent roles
  2. •Set up agent communication
  3. •Configure orchestration
  4. •Implement task delegation
  5. •Test coordination

Copy-Paste Prompts

code
Use @crewai to build multi-agent system with roles

Phase 4: Agent Orchestration

Skills to Invoke

  • •langgraph - LangGraph orchestration
  • •workflow-orchestration-patterns - Orchestration

Actions

  1. •Design workflow graph
  2. •Implement state management
  3. •Add conditional branches
  4. •Configure persistence
  5. •Test workflows

Copy-Paste Prompts

code
Use @langgraph to create stateful agent workflows

Phase 5: Tool Integration

Skills to Invoke

  • •agent-tool-builder - Tool building
  • •tool-design - Tool design

Actions

  1. •Identify tool needs
  2. •Design tool interfaces
  3. •Implement tools
  4. •Add error handling
  5. •Test tool usage

Copy-Paste Prompts

code
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

  1. •Design memory structure
  2. •Implement short-term memory
  3. •Set up long-term memory
  4. •Add entity memory
  5. •Test memory retrieval

Copy-Paste Prompts

code
Use @agent-memory-systems to implement agent memory

Phase 7: Evaluation

Skills to Invoke

  • •agent-evaluation - Agent evaluation
  • •evaluation - AI evaluation

Actions

  1. •Define evaluation criteria
  2. •Create test scenarios
  3. •Measure agent performance
  4. •Test edge cases
  5. •Iterate improvements

Copy-Paste Prompts

code
Use @agent-evaluation to evaluate agent performance

Agent Architecture

code
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