Agent-Skills.md

Agent Skills: Cloudbase Agent (TypeScript)

Build and deploy AI agents with Cloudbase Agent (TypeScript), a TypeScript SDK implementing the AG-UI protocol. Use when: (1) deploying agent servers with @cloudbase/agent-server, (2) using LangGraph adapter with ClientStateAnnotation, (3) using LangChain adapter with clientTools(), (4) building custom adapters that implement AbstractAgent, (5) understanding AG-UI protocol events, (6) building web UI clients with @ag-ui/client, (7) building WeChat Mini Program UIs with @cloudbase/agent-ui-miniprogram.

UncategorizedID: tencentcloudbase/cloudbase-mcp/cloudbase-agent-ts

Repository

tencentcloudbase/cloudbase-mcp
TencentCloudBaseLicense: MIT
981124

Install this agent skill to your local

pnpm dlx add-skill https://github.com/TencentCloudBase/CloudBase-MCP/tree/HEAD/config/allinone/cloudbase/references/cloudbase-agent-ts

Skill Files

Browse the full folder contents for cloudbase-agent-ts.

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config/allinone/cloudbase/references/cloudbase-agent-ts/SKILL.md

Skill Metadata

Name
cloudbase-agent-ts
Description
"Build and deploy AI agents with Cloudbase Agent (TypeScript), a TypeScript SDK implementing the AG-UI protocol. Use when: (1) deploying agent servers with @cloudbase/agent-server, (2) using LangGraph adapter with ClientStateAnnotation, (3) using LangChain adapter with clientTools(), (4) building custom adapters that implement AbstractAgent, (5) understanding AG-UI protocol events, (6) building web UI clients with @ag-ui/client, (7) building WeChat Mini Program UIs with @cloudbase/agent-ui-miniprogram."

Cloudbase Agent (TypeScript)

TypeScript SDK for deploying AI agents as HTTP services using the AG-UI protocol.

Note: This skill is for TypeScript/JavaScript projects only.

When to use this skill

Use this skill for AI agent development when you need to:

  • Deploy AI agents as HTTP services with AG-UI protocol support
  • Build agent backends using LangGraph or LangChain frameworks
  • Create custom agent adapters implementing the AbstractAgent interface
  • Understand AG-UI protocol events and message streaming
  • Build web UI clients that connect to AG-UI compatible agents
  • Build WeChat Mini Program UIs for AI agent interactions

Do NOT use for:

  • Simple AI model calling without agent capabilities (use ai-model-* skills)
  • CloudBase cloud functions (use cloud-functions skill)
  • CloudRun backend services without agent features (use cloudrun-development skill)

How to use this skill (for a coding agent)

  1. Choose the right adapter

    • Use LangGraph adapter for stateful, graph-based workflows
    • Use LangChain adapter for chain-based agent patterns
    • Build custom adapter for specialized agent logic

  2. Deploy the agent server

    • Use @cloudbase/agent-server to expose HTTP endpoints
    • Configure CORS, logging, and observability as needed
    • Deploy to CloudRun or any Node.js hosting environment

  3. Build the UI client

    • Use @ag-ui/client for web applications
    • Use @cloudbase/agent-ui-miniprogram for WeChat Mini Programs
    • Connect to the agent server's /send-message or /agui endpoints

  4. Follow the routing table below to find detailed documentation for each task

Routing

| Task | Read | |------|------| | Deploy agent server (@cloudbase/agent-server) | server-quickstart | | Use LangGraph adapter | adapter-langgraph | | Use LangChain adapter | adapter-langchain | | Build custom adapter | adapter-development | | Understand AG-UI protocol | agui-protocol | | Build UI client (Web or Mini Program) | ui-clients | | Deep-dive @cloudbase/agent-ui-miniprogram | ui-miniprogram |

Quick Start

import { run } from "@cloudbase/agent-server";
import { LanggraphAgent } from "@cloudbase/agent-adapter-langgraph";

run({
  createAgent: () => ({ agent: new LanggraphAgent({ workflow }) }),
  port: 9000,
});