# Agents Crewai

> 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: `vadimcomanescu/agents-crewai` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add vadimcomanescu/agents-crewai`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vadimcomanescu/agents-crewai/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: vadimcomanescu (https://skillmd.com/u/vadimcomanescu)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/vadimcomanescu/agents-crewai

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# CrewAI

Design and run role-based agent teams using CrewAI.

## Quick Start
1) Define agents with clear roles and goals.
2) Define tasks with explicit expected outputs.
3) Choose a process (sequential vs. hierarchical).
4) Run the crew and inspect outputs.

## Minimal Example
```python
from crewai import Agent, Task, Crew, Process

researcher = Agent(role="Researcher", goal="Find 5 key trends")
writer = Agent(role="Writer", goal="Summarize findings")

research = Task(description="Research AI agents", expected_output="5 bullets", agent=researcher)
write = Task(description="Write a summary", expected_output="Short memo", agent=writer, context=[research])

crew = Crew(agents=[researcher, writer], tasks=[research, write], process=Process.sequential)
result = crew.kickoff(inputs={"topic": "AI agents"})
print(result.raw)
```

## Design Guidance
- Keep roles narrow and outputs explicit.
- Use context chaining to pass outputs between tasks.
- Prefer sequential for reliability; hierarchical for delegation-heavy workflows.

## Use Alternatives When
- You need complex graph cycles → consider LangGraph.
- You’re focused on document retrieval → consider LlamaIndex.

## References
- Extended examples: `references/examples.md`