AI导哈

智能体工作流

cargo-ai

getcargohq/cargo-skills

Build and configure AI agents inside Cargo — create an agent, choose its model and temperature, write its prompt, attach knowledge for retrieval (RAG), connect MCP tool servers, manage memories, and deploy releases. Triggers: "create an agent", "make an agent that", "give the agent our docs", "attach this knowledge base", "attach this library to the agent", "add resources to the agent release", "connect an MCP server", "expose our tools as an MCP server", "use Cargo from Claude Desktop or ChatGPT", "change the agent model", "what does the agent remember", "deploy the agent", "the agent is answering wrong". Skip when: uploading the knowledge files themselves — use cargo-content; sending the agent a message or running it over records — use cargo-orchestration.

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安装命令

npx skills add https://github.com/getcargohq/cargo-skills --skill cargo-ai

SKILL.md

Cargo CLI — AI

Agent resource management: creating and configuring agents, attaching knowledge for retrieval-augmented generation (RAG), connecting MCP servers, and managing agent memories.

For using agents (sending messages, multi-turn chat, polling), use cargo-orchestration. For uploading knowledge files and building knowledge libraries (the content domain), use cargo-content. This skill covers how that knowledge attaches to an agent. For workspace administration — folders (used to organize agents and files), users, API tokens, roles, and submitting reports when the CLI fails — use cargo-workspace-management.

See references/response-shapes.md for full JSON response structures. See references/troubleshooting.md for common errors and how to fix them. See references/examples/agents.md for agent CRUD and configuration examples. See references/examples/mcp-servers.md for MCP server creation and management examples.

Bootstrap

Already signed in (cargo-ai whoami returns a workspace)? Skip to the next section.

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