ai-agent-development skill
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
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Install the ai-agent-development skill
A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.
git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git /tmp/agentic-awesome-skills mkdir -p ~/.claude/skills cp -r /tmp/agentic-awesome-skills/plugins/agentic-awesome-skills-claude/skills/ai-agent-development ~/.claude/skills/ai-agent-development
available in every project
In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub
The instructions your agent would load
SKILL.md as published, without the frontmatter. Read it on GitHub
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 architecturePhase 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 agentPhase 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 rolesPhase 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 workflowsPhase 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 toolsPhase 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 memoryPhase 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 performanceAgent Architecture
User Input -> Planner -> Agent -> Tools -> Memory -> Response
| | | |
Decompose LLM Core Actions Short/Long-termQuality Gates
- [ ] Agent logic working
- [ ] Tools integrated
- [ ] Memory functional
- [ ] Orchestration tested
- [ ] Evaluation passing
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