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Blockchains (L3)

# XAI Fees Methodology

## 1. Overview

The xai fees metric measures the total daily transaction fees paid on the Xai blockchain, expressed in USD. This metric answers the question "How much in fees are users paying to transact on the Xai network?" The calculation involves extracting gas consumption and pricing data from Xai blockchain transactions, aggregating to daily totals, and converting to USD using XAI token price feeds.

## 2. Data sources

The calculation uses the following raw data sources:

- **Xai blockchain transaction records**: Complete transaction data from the Xai blockchain including transaction hashes, addresses, gas usage amounts, and effective gas prices paid
- **End-of-day price feeds**: Daily XAI token prices in USD from CoinGecko using the 'xai-blockchain' identifier
- **Token metadata**: XAI token address `0x82af49447d8a07e3bd95bd0d56f35241523fbab1` and symbol information

## 3. Step-by-step calculation

### Component A: Transaction fee extraction
- **Purpose**: Extract and calculate native token gas fees from individual Xai blockchain transactions
- **Logic**: Process all Xai blockchain transactions to identify gas consumption and pricing. For each transaction, extract the `gas_used_amount` (quantity of gas consumed) and `receipt_effective_gas_price` (price per unit of gas in wei). Calculate the native token gas fee by multiplying gas used by gas price, then divide by 1e18 to convert from wei units to XAI token units. Include transaction metadata such as `transaction_hash`, `from_address`, and `to_address` for reference
- **Key fields**: `l3_gas_fee_amount` (calculated fee in native tokens), `block_timestamp`, `gas_used_amount`, `gas_price`, `token_address`

### Component B: Daily fee aggregation  
- **Purpose**: Aggregate transaction-level fees into daily totals
- **Logic**: Group all transactions by day using timestamp truncation to daily granularity. Sum all `l3_gas_fee_amount` values within each day to get total daily fees in native XAI tokens. Maintain classification dimensions including chain identifier, market sector (`blockchains_l3`), and business segment (`blockchain`). Apply incremental processing logic to efficiently update recent data with lookback periods for data reprocessing
- **Key fields**: `fees` (daily aggregated amount), `timestamp` (daily), `chain_id`, `market_sector_id`, `business_segment_id`

### Component C: Price data preparation
- **Purpose**: Obtain daily XAI token prices for USD conversion
- **Logic**: Extract daily XAI token prices from CoinGecko market data using the 'xai-blockchain' identifier. Filter for the appropriate time range and ensure daily timestamp alignment with fee data. Convert price values to appropriate numeric format for calculation
- **Key fields**: `price` (USD price per XAI token), `timestamp` (daily)

### Final aggregation
- **Combining components**: Join daily aggregated fees with corresponding daily XAI token prices using exact timestamp matching on daily boundaries
- **Currency conversion**: Convert native XAI token fees to USD by multiplying the daily `fees` amount by the daily XAI token `price` from CoinGecko
- **Time aggregation**: Maintain daily time boundaries with data filtered through 2025-08-22
- **Final calculation**: The final metric value equals the sum of (daily native token fees × daily XAI price in USD) for each day, with schema validation and gap filling applied through the finalization macro to ensure complete time series data

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Total value users pay to use a protocol (gross fees, user-paid fees).

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