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Agents48k · #2080

ai-agent-development

Facilitates the development of autonomous AI agents and multi-agent systems. Helps orchestrate and build custom agents using tools like CrewAI.

What it does

This guide helps you build 'AI agents,' which are like smart robots that can perform tasks. It covers everything from initial planning to building systems with multiple agents and integrating the tools they use.

When to use it

  • ✓When you want to build an AI robot that thinks and acts on its own.
  • ✓To create a team of AI robots that work together.
  • ✓If you need your AI robots to use other tools or remember things.

Example of what to ask your AI

“Help me plan an AI agent to write articles.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/ai-agent-development/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/ai-agent-development/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The guide outlines a step-by-step process. First, you define what the agent will do. Then, you choose the tools it will use and how it will remember information. Finally, you test if it's working correctly.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill ai-agent-development

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/ai-agent-development/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from 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

Scope and execution

Choose the phases that match the user’s task; this document is an index, not an instruction to run every listed skill. Read a selected skill before using it. Respect repository and user constraints. Cloud calls, host configuration, publishing, destructive operations and spending require the applicable authorization; a workflow checklist does not grant it.

Multi-agent phases describe the product being built. They do not authorize the assistant to spawn or delegate to agents during this task. Use an existing single-agent architecture when appropriate and record evaluation inputs, observed results and limitations.

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

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

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

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ

What is an AI agent?

It's a computer program that can perform tasks autonomously, like an intelligent assistant.

What does 'multi-agent' mean?

It means having several AI agents working together towards a common goal, like a team.

What is agent 'orchestration'?

It's how you organize and control how AI agents interact and execute tasks together.

Details

Original description by the author

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#2080
License
MIT
Updated
10/15/2026

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