This module provides a unified approach to processing protocol data and calculating scores, with protocol-specific customizations applied from a central configuration.
Instead of creating individual files for each protocol's score calculations, this centralized approach uses a JSON configuration file to define protocol-specific adjustments and parameters. This makes the system:
- Scalable - Add new protocols by simply updating the configuration file
- Maintainable - Protocol-specific logic is in one place rather than scattered across files
- Transparent - All adjustments are documented in the configuration file
- Consistent - Core calculation logic is reused across protocols
The configuration file defines:
- Protocol metadata (name, symbol, category, description)
- Protocol-specific query IDs for Dune Analytics
- Adjustments to be applied to the data (e.g., revenue mapping, weights)
- Default settings for protocols that don't have specific configurations
Example:
{
"protocols": {
"chainlink": {
"name": "Chainlink",
"symbol": "LINK",
"category": "Oracle",
"description": "Decentralized oracle network connecting smart contracts to real-world data",
"queries": {
"eqs": {
"query_id": "4953227",
"adjustments": {
"revenue_mapping": {
"ocr": "fm",
"comment": "OCR doesn't generate fees directly, attributing to FM (Price Feeds)"
},
"weights": {
"stability": 0.7,
"diversification": 0.3
}
}
}
}
}
}
}The processor:
- Loads the configuration file
- Applies protocol-specific adjustments to the data
- Calculates scores using the configured parameters
- Generates comprehensive reports
The underlying calculation logic remains consistent, but can be customized through the configuration:
- Stability score: Based on month-over-month revenue volatility
- Diversification score: Based on distribution of revenue sources
- Magnitude score: Based on total revenue amount
- Combined EQS score: Weighted combination adjusted by magnitude
A command-line tool to run the scoring process for any protocol.
- Add an entry to the
protocolssection ofprotocol_config.json:
"uniswap": {
"name": "Uniswap",
"symbol": "UNI",
"category": "DEX",
"description": "...",
"queries": {
"eqs": {
"query_id": "4953227",
"adjustments": {
"weights": {
"stability": 0.7,
"diversification": 0.3
}
}
}
}
}- Run the scoring for the new protocol:
python run_centralized_scoring.py uniswap
Used to reallocate revenue from one source to another:
"revenue_mapping": {
"source_from": "source_to"
}This adds the revenue from source_from to source_to and sets source_from to zero.
Adjust the weights used for combining component scores:
"weights": {
"stability": 0.7,
"diversification": 0.3
}Set reference values for normalization:
"reference_revenue": 5000000The system produces:
- JSON report files (in
scores/{protocol}_report.json) - CSV files with adjusted data (in
scores/{protocol}_adjusted_data.csv) - Console output with summary information
For Chainlink, the configuration specifies:
- OCR revenue should be attributed to FM (Price Feeds)
- Stability should have 70% weight, diversification 30%
Before adjustments:
- Original revenue distribution: fm (39.90%), ocr (57.18%), others (~2.9%)
- EQS Score: 80.29
After adjustments:
- Adjusted revenue distribution: fm (97.08%), ocr (0.00%), others (~2.9%)
- EQS Score: 90.22
The improvement in EQS reflects that Chainlink's revenue is more sustainable when properly attributed to its primary revenue-generating services.