---

name: crewai description: "Routes agents using or contributing to CrewAI, including crews, flows, CLI projects, tools, MCP, memory, RAG, LLM providers, observability, files, multimodal inputs, and repo development." disable-model-invocation: true metadata: disco-role: operating license: MIT

CrewAI

Use this repo skill when the task involves CrewAI, the crewai Python package, the crewai CLI, official CrewAI tools, CrewAI Flows, memory/knowledge/RAG, multimodal file inputs, observability hooks, or contributing to the CrewAI monorepo.

Start Here

• Read Repository provenance before deciding whether this skill matches a current CrewAI checkout or needs refresh.
• Read Installation and dependencies when choosing package extras, optional dependencies, Python versions, or inspection commands.
• Read Troubleshooting for cross-cutting install/import, optional dependency, credentials, CLI/project-root, telemetry, and repo-development failures.
• Run check_crewai_environment.py for a safe local import/version/CLI diagnostic; it does not run crews, call LLMs, start MCP servers, or use credentials.

Route by Task

• Use core-runtime for Agent, Task, Crew, Process, kickoff modes, outputs, guardrails, callbacks, planning, reasoning, checkpoint basics, JSONC crew definitions, and direct-code crew design.
• Use flows-and-events for Flow, @start, @listen, @router, state, routing labels, plotting, persistence, checkpointing, human feedback, event listeners, and event ordering.
• Use cli-and-projects for crewai create, JSON-first and classic project scaffolds, crewai run, train, test, replay, chat, deploy, uv, project templates, and CLI troubleshooting.
• Use tools-and-mcp for official crewai_tools, custom BaseTool or CrewStructuredTool work, MCP adapters, tool publishing, integration tools, optional packages, and credential boundaries.
• Use memory-knowledge-and-rag for Memory, Knowledge, knowledge_sources, RAG loaders, embedding providers, vector stores, RagTool, and reset-memories behavior.
• Use llm-and-providers for LLM, provider model strings, API keys, base URLs, Azure/OpenAI-compatible/Anthropic/Bedrock/Google/Snowflake settings, streaming, tool calls, response models, custom LLMs, and LiteLLM migration.
• Use observability-and-hooks for tracing, telemetry, observability providers, event listeners, LLM/tool hooks, kickoff hooks, output logs, task outputs, and security fingerprints.
• Use files-and-multimodal for crewai-files, input_files, file source resolution, provider file constraints, multimodal agents, upload cache, and file/document tool adjacency.
• Use repo-development only for contributing to this CrewAI checkout: focused tests, docs versioning, Edge docs edits, frozen snapshot rules, workspace metadata, and safe native verification selection.

Common Decisions

• Prefer JSON-first projects from crewai create crew <name> unless the user is maintaining an existing classic Python/YAML crew or needs decorator-heavy customization.
• Treat custom:<name> tools and {"python": "module.attribute"} JSONC references as trusted-code boundaries; inspect before running projects from untrusted sources.
• Do not run LLM-backed crews, hosted deploy/login commands, MCP servers, network-backed tools, or credential-bound integrations just to inspect a project. Use the bundled diagnostic scripts first.
• Use provider-specific sub-skills for optional dependency and credential choices instead of installing all extras or assuming all integrations are available.
• For repo docs edits, modify only docs/edge/<lang>/...; do not edit docs/v*/ frozen snapshots or delete/rename docs/images/ assets outside release-freeze work.

Safe Diagnostics

• python scripts/check_crewai_environment.py --json reports installed CrewAI package versions, top-level import results, and CLI command names.
• python sub-skills/core-runtime/scripts/validate_crew_definition.py --help explains static JSONC crew checks without importing project custom code.
• python sub-skills/flows-and-events/scripts/validate_flow_graph.py --help explains static flow graph checks without calling kickoff().
• python sub-skills/cli-and-projects/scripts/inspect_crewai_cli.py --help explains CLI/project layout checks that avoid running crews or deploy/login flows.
• python sub-skills/repo-development/scripts/select_native_tests.py --help suggests focused maintainer checks from changed paths without running them.

Refresh Triggers

Run refresh-repo-skill before relying on this skill if the current CrewAI checkout has a different commit than Repository provenance, package versions or CLI entry points changed, docs/edge/en/ workflows changed materially, or major source roots such as lib/crewai/src/crewai, lib/cli/src/crewai_cli, lib/crewai-tools/src/crewai_tools, or lib/crewai-files/src/crewai_files moved.