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

# Bonding Curves

<figure><img src="/files/rJeI4JE2ZHFvzwDFnE3Z" alt=""><figcaption></figcaption></figure>

LIKN introduces a carefully designed price curve that makes UA highly engaging and strategic during the primary market issuance phase. The initial price is set low to encourage user participation, with a practical and balanced upward price trajectory. This approach not only creates investment value for UA but also enhances market liquidity and engagement. Notably, LIKN is pioneering the first UA project platform in the crypto space to implement multiple pricing curves and issuance formats, establishing a new paradigm for UA issuance.

$$
y = a\*(\cfrac{x-b}{\sqrt{c + (x-b)^2}} +1)
$$

```javascript
uint256 private a = 150000000000000;     // a = fix_price / 2
uint256 private b = 400000000;           // b = 0
uint256 private c = 20000000000000000;   // c = 0
```

| The Nth Token | Price(ETH)       |
| ------------- | ---------------- |
| 1             | 0.0000085786438  |
| 100000        | 0.0000085825734  |
| 1000000       | 0.0000086180587  |
| 10000000      | 0.0000089849613  |
| 100000000     | 0.00001431989494 |
| 400000000     | 0.00015          |
| 800000000     | 0.00029142135623 |


---

# 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.likn.ai/likn-studio/bonding-curves.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.