Agent skill · AI & Agents

crewai-multi-agent

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.

Orchestra-Researchgithub.com/Orchestra-ResearchGitHub ↗
claude-codecodexMIT
Install
npx skills add Orchestra-Research/AI-Research-SKILLs --skill crewai --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 13 KB
Bundled scripts: none
Version: 1.0.0
Declared author: Orchestra Research
Requires: [crewai>=1.2.0, crewai-tools>=1.2.0]
Path: 14-agents/crewai/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 11,391
Language: TeX
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 #

What's inside
Steps it walks through
  1. When to use CrewAI
  2. Quick start
  3. Installation
  4. Create project with CLI
  5. Simple crew (code-only)
  6. Core concepts
  7. Agents - Autonomous workers
  8. Tasks - Units of work
  9. Crews - Teams of agents
  10. Process types
  11. Sequential (default)
  12. Hierarchical
  13. Using tools
  14. Built-in tools (50+)
Ships with 3 files
  • references/flows.md
  • references/tools.md
  • references/troubleshooting.md
Commands it runs
Core framework
pip install crewai
With 50+ built-in tools
pip install 'crewai[tools]'
Create new crew project
crewai create crew my_project
cd my_project
Install dependencies
crewai install
Run the crew
More from AI-Research-SKILLs
All skills →
About this skill
What does the crewai-multi-agent skill do?

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.

How do I install it?

Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill crewai --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going