A collection of skills for AI coding agents that teach best practices for building with CrewAI. Skills follow the Agent Skills format.
概览
A collection of skills for AI coding agents that teach best practices for building with CrewAI. Skills follow the Agent Skills format. CrewAI architecture decisions and project scaffolding. Covers choosing the right abstraction (LLM.call() vs Agent.kickoff() vs Crew.kickoff() vs Flow), CLI scaffolding, YAML configuration, wiring @CrewBase crews, writing Flows with @start/@listen, conversational Flows with handle_turn(), and variable interpolation. - Starting a new CrewAI project - Choosing between abstraction levels - Scaffolding with crewai create flow - Setting up agents.yaml and tasks.yaml - Wiring crew.py or main.py - Building experimental conversational Flows - Debugging common setup issues CrewAI agent design and configuration. Covers the Role-Goal-Backstory framework, LLM selection, tool assignment, execution tuning (max_iter, max_rpm, max_execution_time), memory and knowledge sources, guardrails, and YAML vs code configuration.
README
CrewAI Skills
A collection of skills for AI coding agents that teach best practices for building with CrewAI. Skills follow the Agent Skills format.
Available Skills
getting-started
CrewAI architecture decisions and project scaffolding. Covers choosing the right abstraction (LLM.call() vs Agent.kickoff() vs Crew.kickoff() vs Flow), CLI scaffolding, YAML configuration, wiring @CrewBase crews, writing Flows with @start/@listen, conversational Flows with handle_turn(), and variable interpolation.
Use when:
- Starting a new CrewAI project
- Choosing between abstraction levels
- Scaffolding with
crewai create flow - Setting up agents.yaml and tasks.yaml
- Wiring crew.py or main.py
- Building experimental conversational Flows
- Debugging common setup issues
design-agent
CrewAI agent design and configuration. Covers the Role-Goal-Backstory framework, LLM selection, tool assignment, execution tuning (max_iter, max_rpm, max_execution_time), memory and knowledge sources, guardrails, and YAML vs code configuration.
Use when:
- Creating or configuring CrewAI agents
- Choosing role, goal, and backstory
- Assigning tools or selecting LLMs
- Tuning agent parameters
- Setting up knowledge sources or memory
- Debugging agent behavior
design-task
CrewAI task design and configuration. Covers writing effective descriptions and expected output, task dependencies with context, structured output (output_pydantic, output_json, output_file), guardrails, human-in-the-loop review, and async execution.
Use when:
- Creating or configuring CrewAI tasks
- Writing task descriptions and expected output
- Setting up task dependencies
- Configuring structured output formats
- Adding guardrails or human review
- Debugging task execution issues
Installation
In Claude Code, add this marketplace and install the plugin:
/plugin marketplace add crewAIInc/skills
/plugin install crewai-skills@crewai-plugins
The first command registers the marketplace from this repo’s .claude-plugin/marketplace.json. The second installs the crewai-skills plugin from the crewai-plugins marketplace.
To pin to a specific branch or tag:
/plugin marketplace add crewAIInc/skills
Skill Structure
Each skill contains:
SKILL.md- Instructions for the agentreferences/- Supporting documentation (tools catalog, MCP servers, structured output patterns, etc.)
License
MIT
推荐工具
换一个关键词,或者移除筛选条件。
安装
npx skillfish add crewaiinc/skills