# Rating Breakdown

The Composite Risk Score is a weighted aggregate of six risk dimensions.

| Dimension           | API Field             | Weight | Scale |
| ------------------- | --------------------- | ------ | ----- |
| Smart Contract Risk | `smart_contract_risk` | 25%    | 0–10  |
| Counterparty Risk   | `counterparty_risk`   | 20%    | 0–10  |
| Credit Risk         | `credit_risk`         | 15%    | 0–10  |
| Liquidity Risk      | `liquidity_risk`      | 15%    | 0–10  |
| Oracle Risk         | `oracle_risk`         | 15%    | 0–10  |
| Liquidity Trap Risk | `liquidity_trap_risk` | 10%    | 0–10  |

All dimensions are scored 0–10 where **higher = riskier**. A dimension may be `null` (N/A) if insufficient data exists — in that case its weight is redistributed proportionally across the remaining dimensions.

#### Master Formulae

**Step 1 — Linear Weighted Score**

```
C_L = Σ (Di × Wi)
```

Where `Di` is the dimension score and `Wi` is its normalized weight (after excluding N/A dimensions).

**Step 2 — Exponential Decay (always applied)**

```
C_E = 1 + 9 × ((C_L − 1) / 9) ^ 1.5
```

The exponential decay with γ = 1.5 penalizes mid-range scores more severely — mediocre protocols score visibly worse than a simple linear average would suggest.

**Step 3 — Risk Level**

The composite score is inverted to derive the risk level:

```
safety = 10 − composite_score
```

| Safety Score | Risk Level |
| ------------ | ---------- |
| 8.5 – 10.0   | Very Low   |
| 7.0 – 8.4    | Low        |
| 5.5 – 6.9    | Moderate   |
| 4.0 – 5.4    | Elevated   |
| 1.0 – 3.9    | High       |


---

# 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.diapleo.com/documentation/getting-started/rating-breakdown.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.