> For the complete documentation index, see [llms.txt](https://gmgai.gitbook.io/gmgai-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://gmgai.gitbook.io/gmgai-docs/3-he-xin-sheng-tai/3.1-ai-agent-zhi-hui-zi-chan-pei-zhi-sheng-tai.md).

# 3.1 AI Agent 智慧資產配置生態

作為生態核心服務引擎，依託自主研發的 Web4 原生 AI Agent 自主決策系統，深度融合大數據分析、機器學習、深度學習與智慧風控演算法，實現 7×24 小時不中斷全自動資產配置、動態調倉、智慧風控、收益再投資與風險自動隔離的全流程閉環管理。為 C 端用戶提供低門檻、高穩定性服務，為機構客戶提供定制化專戶管理，兼顧收益性與安全性，成為生態核心用戶抓手與收益來源。


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# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://gmgai.gitbook.io/gmgai-docs/3-he-xin-sheng-tai/3.1-ai-agent-zhi-hui-zi-chan-pei-zhi-sheng-tai.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
