# Agents Crewai

Multi-agent orchestration framework for autonomous AI collaboration.

- Repository: https://github.com/davila7/claude-code-templates (33041 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add davila7/claude-code-templates --skill agents-crewai -g -a claude-code -y`
Codex: `npx skills add davila7/claude-code-templates --skill agents-crewai -g -a codex -y`
Cursor: `npx skills add davila7/claude-code-templates --skill agents-crewai -g -a cursor -y`
Gemini CLI: `npx skills add davila7/claude-code-templates --skill agents-crewai -g -a gemini-cli -y`

## Description

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# CrewAI - Multi-Agent Orchestration Framework

Build teams of autonomous AI agents that collaborate to solve complex tasks.

## When to use CrewAI

**Use CrewAI when:**
- Building multi-agent systems with specialized roles
- Need autonomous collaboration between agents
- Want role-based task delegation (researcher, writer, analyst)
- Require sequential or hierarchical process execution
- Building production workflows with memory and observability
- Need simpler setup than LangChain/LangGraph

**Key features:**
- **Standalone**: No LangChain dependencies, lean footprint
- **Role-based**: Agents have roles, goals, and backstories
- **Dual paradigm**: Crews (autonomous) + Flows (event-driven)
- **50+ tools**: Web scraping, search, databases, AI services
- **Memory**: Short-term, long-term, and entity memory
- **Production-ready**: Tracing, enterprise features

**Use alternatives instead:**
- **LangChain**: General-purpose LLM apps, RAG pipelines
- **LangGraph**: Complex stateful workflows with cycles
- **AutoGen**: Microsoft ecosystem, multi-agent conversations
- **LlamaIndex**: Document Q&A, knowledge retrieval

## Quick start

### Installation

```bash
# Core framework
pip install crewai

# With 50+ built-in tools
pip install 'crewai[tools]'
```

### Create project with CLI

```bash
# Create new crew project
crewai create crew my_project
cd my_project

# Install dependencies
crewai install

# Run the crew
crewai run
```

### Simple crew (code-only)

```python
from crewai import Agent, Task, Crew, Process

# 1. Define agents
researcher = Agent(
    role="Senior Research Analyst",
    goal="Discover cutting-edge developments in AI",
    backstory="You are an expert analyst with a keen eye for emerging trends.",
    verbose=True
)

writer = Agent(
    role="Technical Writer",
    goal="Create clear, engaging content about technical topics",
    backstory="You excel at explaining complex concepts to general audiences.",
    verbose=True
)

The rest: https://github.com/davila7/claude-code-templates/blob/HEAD/cli-tool/components/skills/ai-research/agents-crewai/SKILL.md