domains / families / agent-tooling / crewai

crewai

combined

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. Expert in CrewAI - the leading role-based multi-agent framework

When to use

• 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
• **Standalone**: No LangChain dependencies, lean footprint
• **Role-based**: Agents have roles, goals, and backstories

When not to use

• 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.

Skill page

Conflict

Both copies describe the same CrewAI framework, but they emphasize different, non-overlapping implementation paths. The Orchestra-Research copy is a code-first guide focused on inline Python definitions, CLI project creation, and core object parameters. The sickn33 copy is a configuration-first guide that emphasizes YAML-based agent/task definitions, the @CrewBase decorator pattern, and specific features like the 'planning' flag and 'manager_llm' configuration. Neither copy is a strict reproduction of the other; combining them provides a more complete picture of how to structure a CrewAI project (either via code or YAML) and which advanced features are available.