Tutorial: Build a Customer Service Agent
Build a customer service Agent in your team that cites a knowledge base and calls web search
After completing this tutorial, you will have a customer service Agent that answers product questions, cites internal documentation, queries the web when needed, and shows run sources.
Prerequisites
You are logged in to Clouisle; the current team has an enabled chat model; you have a usable knowledge base, or create one first by following Create a knowledge base. Web search requires the server-side TAVILY_API_KEY configuration.
Final Result
The customer service Agent is in the Published state, with a system prompt, one linked knowledge base, the web search tool, and at least one suggested question.

Step 1: Create the Agent
- Open Apps > Create app > Agent.
- Set the name to
客服助手and describe the service scope in the description. - Select a
chatmodel authorized for the team. - Save in Agent settings.

Step 2: Write the Prompt
In Prompt, enter:
你是 Clouisle 产品客服助手。
优先根据关联知识库回答,并在有来源时给出引用。
知识库没有足够信息时,明确说明不确定,不要编造版本、配置或价格。
只有用户要求最新外部信息时才使用网页搜索。
回复使用简体中文,先给结论,再给步骤。Save and send a product question in the preview.
Step 3: Link the Knowledge Base
- On the Knowledge base card, select Add.
- Select the target knowledge base.
- Use
hybridretrieval with Top K of5and a threshold of0.3. - Save.

Step 4: Enable Web Search
- In Tools, select Add.
- Select the built-in
web_search. - If Configuration required appears, contact an administrator to configure the Tavily API Key.
- Save and test a question that needs external information.
Step 5: Publish & Accept
- Verify citations with an internal documentation question.
- Verify tool calls with a time-sensitive question.
- Verify refusal or uncertainty statements with a sensitive question not covered by the knowledge base.
- Select Publish and open the Public page.
- In Agent Logs, confirm conversations, sources, tool results, and Token usage.
Acceptance criteria
Internal questions have sources; external questions trigger web_search only when needed; tool failures show errors instead of faked success; the Agent public page supports continued multi-turn conversations.
How is this guide?