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

# Background

Given the rise of recent NFT games such as **My Crypto Heroes, Gods Unchained, Decentraland** or **Axie Infinity**, the design team realized something in these projects:

* Not all of them have a native token/coin.
* Prices vary greatly with the fluctuation of the market.
* Slow confirmation time.
* Horrendous gas fee.

The price volatility of cryptocurrencies is a major deterrent for mass adoption. The inconvenience from the lack of a stable, easy to predict token that somewhat stays at a fixed price that can be used in any transaction but in the core still decentralized is unneglectable. Many find that even stablecoins like USDT or BUSD, although are stable, have to be collateralized with real-life fiat or equivalent and therefore, still centralized.

Thus, we decided to create an algorithmic stablecoin that can be adopted into our games, creating both a supply and consumption demand for the tokens, allowing a continuous and stable cash flow within the ecosystem.

***Contents are subjected to changes without prior notices\****

###


---

# 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:

```
GET https://monsterslayer.gitbook.io/monsterslayer-finance/background.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
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.