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

# Introduction

Panda Coin ($Pandaz) isn’t just another cryptocurrency, it’s an entire experience. Think pandas, meme culture, and blockchain innovation all rolled into one. Inspired by the cute fluffy bear that everyone loves and from movie fame, Pandaz takes the magic of fantasy and mixes it with real-world utility.\
This isn’t just a token. It’s a full-on ecosystem built to engage, reward, and entertain. With a total supply of 100 billion tokens, Pandaz lives on the Solana blockchain, bringing top-tier security, smooth integration, and a solid foundation for long-term growth.\
What makes it different? Pandaz isn’t just about holding a token, it’s about being part of a movement. By blending blockchain technology, gamification, and a strong community-driven approach, Pandaz offers something unique: a fun, interactive space where users can get involved, earn rewards, and enjoy the ride.


---

# 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://docs.pandamoonlabs.com/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.
