ai-agent-development
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.
Skill by manu14357
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: productivity, agent-building
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What's inside
- Skill 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.
- License
- MIT
- Instructions
- 171 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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 ``` 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 ``` 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 ``` 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 ``` 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 ``` 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
From manu14357/zskills, MIT.
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Signals
- Stars
- 16
- Forks
- 2
- Open issues
- 0
- Last commit (this folder)
- May 6, 2026 (5 months ago)
- Last release
- Apr 26, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/manu14357/zskills
- Website
- zskills.vercel.app
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
ai-agent-development skill. Agent Mart. https://agentmart.dev/skills/manu14357-ai-agent-development (last updated 2026-10-24)