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name: core-runtime description: "Guides agents working with CrewAI core runtime objects, including agents, tasks, crews, processes, kickoff modes, outputs, guardrails, callbacks, planning, reasoning, checkpoint basics, and JSONC crew definitions." disable-model-invocation: true metadata: disco-role: operating license: MIT

Core Runtime

Use this sub-skill when the task is to design, debug, migrate, or validate CrewAI Agent, Task, Crew, Process, CrewOutput, or TaskOutput usage in direct Python code or JSONC crew projects.

Route First

• For object signatures, required fields, process values, kickoff variants, outputs, callbacks, guardrails, planning, reasoning, and checkpoint basics, read references/api-reference.md.
• For direct-code assembly, sequential and hierarchical crews, output handling, guardrails, callback placement, planning/reasoning, and checkpoint-safe patterns, read references/workflows.md.
• For JSONC project runtime fields, agent files, task entries, callback/custom-tool trust boundaries, and migration between Python and JSONC, read references/jsonc-projects.md.
• For common symptoms and fixes, including missing agent/task fields, forward task context, hierarchical manager requirements, output model confusion, guardrail retries, callback trust, and checkpoint/training mixups, read references/troubleshooting.md.
• To statically check a JSONC crew definition without importing project tools or running LLMs, run scripts/validate_crew_definition.py with --help first.

Boundaries

• Stay here for core runtime composition, kickoff behavior, task dependencies, outputs, guardrails, callbacks, planning/reasoning, security/checkpoint basics, and JSONC-vs-code construction choices.
• Use ../flows-and-events/SKILL.md for Flow, @start, @listen, @router, event graph routing, flow persistence, and flow plotting.
• Use ../cli-and-projects/SKILL.md for project scaffolding, crewai run, crewai train, crewai test, crewai replay, crewai checkpoint, and other CLI command details.
• Use ../tools-and-mcp/SKILL.md for official tools, custom tools, MCP adapters, and tool publishing.
• Use ../llm-and-providers/SKILL.md for provider credentials, LLM provider options, model IDs, base URLs, streaming provider compatibility, and LiteLLM migration details.
• Use ../memory-knowledge-and-rag/SKILL.md for memory scopes, knowledge sources, embeddings, RAG clients, vector stores, and retrieval depth.
• Return to ../../SKILL.md when a request spans multiple CrewAI capability areas and needs root routing context.