> For the complete documentation index, see [llms.txt](https://stars-ai-docs.gitbook.io/stars-ai-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stars-ai-docs.gitbook.io/stars-ai-docs/introduction.md).

# Introduction

<figure><img src="/files/6pwZzYrK1BEevXipkXJX" alt=""><figcaption></figcaption></figure>

STARS AI is developed to predict market sentiment analysis through User Behaviors and Price Action, allowing users to obtain information which they can utility for their various purposes. AI will be trained based on historical data of users and price line history, along with market movements to provide the most accurate information to support predictions.

STARS AI is a revolution in the BNB Chain Ecosystem. The purpose of the project is to provide AI tools for users to apply to trading and prediction, thereby creating value and profit.

## Links

CoinMarketCap (coming soon)

CoinGecko&#x20;

{% embed url="<https://www.geckoterminal.com/zh/bsc/pools/0xadafd22dd70ad7aa37ab5955dbbff44dccbc6d02>" %}


---

# 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://stars-ai-docs.gitbook.io/stars-ai-docs/introduction.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.
