crewai

Design and orchestrate multi-agent AI systems with the CrewAI framework.

2|Updated Feb 6, 2026

Search Tags:#workflow automation #ai agents #multi-agent #orchestration #crewai #role-based agents

Ready to run

npx skills add https://github.com/bcastelino/agent-skills-kit --skill crewai-bcastelino

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: crewai
Source: https://github.com/bcastelino/agent-skills-kit/tree/main/skills/crewai
Command: npx skills add https://github.com/bcastelino/agent-skills-kit --skill crewai-bcastelino

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the creation and management of multi-agent AI systems using the CrewAI framework, enabling complex workflows through role-based agent collaboration.

Core Features & Use Cases

Agent Definition: Design agents with specific roles, goals, and backstories.
Task Orchestration: Define tasks with dependencies and expected outputs.
Process Management: Utilize sequential, hierarchical, or planning-based execution flows.
Use Case: Build an AI research team where a researcher agent gathers information, an analyst agent processes it, and a writer agent creates a report, all coordinated by the CrewAI framework.

Quick Start

Use the crewai skill to define a basic crew with a researcher and writer agent for a given topic.

Frequently Asked Questions about crewai

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I orchestrate multi-agent AI systems for complex workflow automation?▼

Multi-agent AI systems are orchestrated by defining role-based agents, assigning tasks with dependencies, and selecting execution processes like sequential, hierarchical, or planning flows. This coordinates agents to collaborate on complex workflows automatically.

What is the best way to build an AI research team with role-based agents?▼

Building an AI research team involves defining specific roles, goals, and backstories for each agent. You create a researcher to gather information, an analyst to process it, and a writer to generate reports, coordinating them via structured execution processes.

Do I need Python to use CrewAI for multi-agent orchestration?▼

Yes, Python 3.10+ and the crewai package are required to use this multi-agent orchestration framework. These dependencies are necessary for running agent-based workflow automation and defining execution processes.

Can I use hierarchical execution processes for task orchestration in AI agents?▼

Yes, task orchestration supports hierarchical execution processes alongside sequential and planning-based flows. You define tasks with dependencies and expected outputs, allowing agents to process work in a structured, managed hierarchy.

When should I use planning-based execution flows instead of sequential processes for AI agents?▼

Use planning-based execution flows when multi-agent workflows require dynamic task coordination, whereas sequential processes execute tasks in a fixed order. Planning allows agents to adapt task dependencies, while hierarchical processes delegate tasks for complex collaboration.