> For the complete documentation index, see [llms.txt](https://docs.liquity.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.liquity.org/liquity-v1-cn/documentation/resources.md).

# Technical Resources

A technical system summary including contract descriptions, function descriptions, and more is available in the [**Liquity README**](https://github.com/liquity/beta/blob/main/README.md).

## Technical papers

#### [Whitepaper](https://docsend.com/view/bwiczmy)

[**Scalable Reward Distribution with Compounding Stakes**](https://github.com/liquity/liquity/blob/master/papers/Scalable_Reward_Distribution_with_Compounding_Stakes.pdf) (see this [article](https://medium.com/liquity/scaling-liquitys-stability-pool-c4c6572cf275) for a simpler introduction)

#### [Efficient Order-Preserving Redistribution of Troves](https://github.com/liquity/liquity/blob/master/papers/Efficient_Order-Preserving_Redistribution_of_Troves.pdf)

## Economic modelling and simulation

#### [Liquity Market Risk Assessment by Gauntlet Networks](https://liquity-report.gauntlet.network/)

#### [Macroeconomic Model of Liquity by Prof. Yulin Liu](https://colab.research.google.com/drive/1AyhFfE_EKCcMO6HeG04Se3hbraTxODWU?usp=sharing)

## Security audits

[**Trail of Bits Security Assessment**](https://github.com/trailofbits/publications/blob/master/reviews/Liquity.pdf) January 2021

[**Audit by Coinspect**](https://www.coinspect.com/liquity-audit/) March 2021

## Code base

#### [Github Repository](https://github.com/liquity/liquity)


---

# 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://docs.liquity.org/liquity-v1-cn/documentation/resources.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.