CrewAI Engineering: core products, platform infrastructure, developer experience, and engineering tooling.
CrewAI is the engineering team behind the CrewAI framework, and its skills cover the full arc of building AI agent systems: starting and scaffolding projects, designing agents and tasks, wiring up tools and MCP servers, building stateful Flows with persistence and human feedback, calling deployed crews over HTTP, and getting projects onto CrewAI AMP. What stands out is how closely the skills track the current crewAI 1.15.x API, including guidance that corrects outdated 0.x patterns that coding assistants often recall.
Skills
10 skills · 48 stars · MIT
Ask Docs Query the official CrewAI documentation for answers.
Build Flow Building CrewAI Flows on crewai 1.15.x: structured (Pydantic) vs dict state and state.id, @start/…
Call Deployed Crew Calling a crew or flow deployed on CrewAI AMP over HTTP: the bearer token and deployment URL, GET…
Check Crewai Api Current crewai 1.15.x API versus the 0.x API that coding assistants remember: imports, Agent/Task…
Connect Tools And Mcp Giving crewAI agents tools and MCP servers on crewai 1.15.x: custom BaseTool with args_schema and…
Deploy To Amp Getting a CrewAI crew or flow onto CrewAI AMP: the project shape the build expects (uv.lock, [too…
Design Agent CrewAI agent design and configuration.
Design Task CrewAI task design and configuration.
Getting Started CrewAI architecture decisions and project scaffolding.
Test Crewai Project Deterministic, offline testing of CrewAI crews and flows with pytest: a stub BaseLLM (shipped in…