> For the complete documentation index, see [llms.txt](https://docs.rubyscore.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rubyscore.io/how-rubyscore-works/reputation-scoring.md).

# Reputation Scoring

**Reputation scoring in RubyScore** is a set of methods and models that turn on-chain activity into reputation signals and scores. Based on these signals, **three independent products** are formed:

#### 1) Multichain Reputation Score (MRS)

A unified score that **aggregates a wallet’s behavior across multiple networks**.\
To increase MRS, a wallet should demonstrate **regular and diverse activity across different chains** (not just one-off actions for a single drop).

#### 2) Proof-of-Human ID (PoH ID)

A **local proof of “human-ness”** based on on-chain actions **within a specific ecosystem** (network or project).\
For each ecosystem, a **custom formula** (metric weights and thresholds) is configured on request to determine the PoH ID levels.

#### 3) Score Level

**Achievement levels for a wallet** based on on-chain activity within a specific ecosystem.\
Level progression depends on **sustained engagement over time**: the higher the level, the more active and consistent the behavior in that network/project.

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### Key metrics (non-exhaustive)

* **Amount on balance**
* **Total gas spent**
* **Transactions with unique contracts**
* **Transactions on different days**
* **Transactions on different weeks**
* **Transactions on different months**
* **Transaction volume**
* **Number of transactions**

Additionally considered: diversity of interaction categories (DeFi/NFT/Bridge/DAO), depth of interaction sequences (e.g., bridge → deposit → swap → LP → vote), temporal stability, economic rationality, and anti-manipulation signals (filtering scripted and repetitive patterns).