> For the complete documentation index, see [llms.txt](https://cypher-hub.gitbook.io/cypher-hub/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cypher-hub.gitbook.io/cypher-hub/how-it-works-from-content-to-rewards.md).

# How It Works: From Content to Rewards

CC rewards are built around **Qualified Engagement (QE)**.

We believe that 10 comments from real enthusiasts are more valuable than 10,000 likes from bot farms.

{% hint style="info" %}
On CypherHub, value comes from relevant, organic attention.

Not from inflated surface metrics.
{% endhint %}

### Integrity Radar

Integrity Radar acts as an AI-driven arbitration layer.

It analyzes every publication across multiple parameters.

#### What the system evaluates

* **Semantic analysis** — how deeply the author explores the campaign theme
* **Audience audit** — verification of the profiles interacting with the post, including account age, activity history, and interests
* **Anomaly detection** — instant detection of spikes in non-organic traffic

### Qualified Engagement (QE)

QE is the fundamental unit of value in CypherHub.

Rewards are not distributed simply per post.

They are distributed based on the amount of QE a publication generates.

#### Example

A post with 100 views from targeted Web3 investors may earn more than a post with 5,000 views from random, non-relevant users.


---

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