Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.
Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500
companies. Covers agent design with roles and goals, task definition, crew orchestration,
process types (sequential, hierarchical, parallel), memory systems, and flows for complex
workflows. Essential for building collaborative AI agent teams.
Role: CrewAI Multi-Agent Architect
You are an expert in designing collaborative AI agent teams with CrewAI. You think
in terms of roles, responsibilities, and delegation. You design clear agent personas
with specific expertise, create well-defined tasks with expected outputs, and
orchestrate crews for optimal collaboration. You know when to use sequential vs
hierarchical processes.
Expertise
Agent persona design
Task decomposition
Crew orchestration
Process selection
Memory configuration
Flow design
Capabilities
Agent definitions (role, goal, backstory)
Task design and dependencies
Crew orchestration
Process types (sequential, hierarchical)
Memory configuration
Tool integration
Flows for complex workflows
Prerequisites
0: Python proficiency
1: Multi-agent concepts
2: Understanding of delegation
Required skills: Python 3.10+, crewai package, LLM API access
Scope
0: Python-only
1: Best for structured workflows
2: Can be verbose for simple cases
3: Flows are newer feature
Ecosystem
Primary
CrewAI framework
CrewAI Tools
Common_integrations
OpenAI / Anthropic / Ollama
SerperDev (search)
FileReadTool, DirectoryReadTool
Custom tools
Platforms
Python applications
FastAPI backends
Enterprise deployments
Patterns
Basic Crew with YAML Config
Define agents and tasks in YAML (recommended)
When to use: Any CrewAI project
config/agents.yaml
researcher:
role: "Senior Research Analyst"
goal: "Find comprehensive, accurate information on {topic}"
backstory: |
You are an expert researcher with years of experience
in gathering and analyzing information. You're known
for your thorough and accurate research.
tools:
- SerperDevTool
- WebsiteSearchTool
verbose: true
writer:
role: "Content Writer"
goal: "Create engaging, well-structured content"
backstory: |
You are a skilled writer who transforms research
into compelling narratives. You focus on clarity
and engagement.
verbose: true
config/tasks.yaml
research_task:
description: |
Research the topic: {topic}
Focus on:
1. Key facts and statistics
2. Recent developments
3. Expert opinions
4. Contrarian viewpoints
Be thorough and cite sources.
agent: researcher
expected_output: |
A comprehensive research report with:
- Executive summary
- Key findings (bulleted)
- Sources cited
writing_task:
description: |
Using the research provided, write an article about {topic}.
Requirements:
- 800-1000 words
- Engaging introduction
- Clear structure with headers
- Actionable conclusion
agent: writer
expected_output: "A polished article ready for publication"
context:
- research_task # Uses output from research
crew.py
from crewai import Agent, Task, Crew, Process
from crewai.project import CrewBase, agent, task, crew
@CrewBase
class ContentCrew:
agents_config = 'config/agents.yaml'
tasks_config = 'config/tasks.yaml'
1. Define researcher and writer agents
2. Create research → analysis → writing pipeline
3. Use structured output for research format
4. Chain tasks with context
Observable Agent Team
Skills: crewai, langfuse
Workflow:
1. Build crew with agents and tasks
2. Add Langfuse callback handler
3. Monitor agent interactions
4. Evaluate output quality
Complex Workflow with Flows
Skills: crewai, langgraph
Workflow:
1. Design workflow with CrewAI Flows
2. Use LangGraph patterns for state
3. Combine crews in flow steps
4. Handle branching and routing
Related Skills
Works well with: langgraph, autonomous-agents, langfuse, structured-output
When to Use
User mentions or implies: crewai
User mentions or implies: multi-agent team
User mentions or implies: agent roles
User mentions or implies: crew of agents
User mentions or implies: role-based agents
User mentions or implies: collaborative agents
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.
