Rogue is quite intensive in its operation. We fetch fresh liquidity pools, retrieve "historical prices" (typically no more than a few minutes old), and begin live price fetching. Due to rate and API limits, we must bundle our calls. What does this entail? We receive live price data and use it to construct our own candlestick data (OHLC) instead of relying solely on price plots.
It has also been a struggle to find competent data providers who deliver clean data in a way we can utilize properly. Many providers have abysmal documentation or inconsistent endpoints, which turns what should be a fairly straightforward job into a PITA (pain in the ass).
The downside to our approach is that it requires a robust backend. The upside is that, with this data, we have complete freedom to analyze and manipulate it as needed. Eventually, when we set up our own nodes, we will be able to move from third-party to in-house RPC and data endpoints.
Once the data is prepared, our criteria are checked against live prices. When a signal is generated based on our technical requirements, a security scan and metadata scan are conducted. This process ultimately produces a signal that includes all the standard data you'd expect from any other token scanner, albeit packaged in a more concise way.
Chain-agnostic...
Rogue Feature Audit (partial)
Configuration
✅ Environment variable loading
✅ Basic configuration
✅ Configuration validation
❌ Multiple environment support
✅ Secret management
❌ Configuration hot reloading
Telegram Service
✅ Bot initialization
✅ Basic message sending
✅ Error handling
❌ Command handling
❌ User interaction
❌ Message rate limiting
❌ Message formatting helpers
❌ Interactive commands
Price Service
✅ Price history tracking
✅ Active pair management
✅ Basic error handling
✅ Price aggregation
❌ Volume tracking
❌ Market depth analysis
✅ Price alert thresholds
❌ Historical data storage
Pair Lifecycle Manager
✅ Pair tracking
✅ Liquidity monitoring
✅ Basic error handling
❌ Advanced pair filtering
❌ Pair metadata tracking
❌ Historical liquidity data
⚠️ Pair scoring system
⚠️ Risk assessment
Price Analyzer
✅ Basic strategy implmentation
✅ Basic crossover detection
❌ Multiple timeframe analysis
❌ Volume analysis integration
❌ Trend strength calculation
❌ Support/Resistance detection
❌ Pattern recognition
❌ Risk management
Logging System
✅ Basic logging levels
✅ Timestamp formatting
✅ Error logging
❌ Log rotation
❌ Log persistence
❌ Performance logging
❌ Log aggregation
❌ Request/Response logging
Error Handling
✅ Basic error types
✅ Error logging
❌ Error reporting service
❌ Error aggregation
❌ Alert thresholds
❌ Error recovery strategies
❌ Circuit breakers
❌ Fallback mechanisms
It has also been a struggle to find competent data providers who deliver clean data in a way we can utilize properly. Many providers have abysmal documentation or inconsistent endpoints, which turns what should be a fairly straightforward job into a PITA (pain in the ass).
The downside to our approach is that it requires a robust backend. The upside is that, with this data, we have complete freedom to analyze and manipulate it as needed. Eventually, when we set up our own nodes, we will be able to move from third-party to in-house RPC and data endpoints.
Once the data is prepared, our criteria are checked against live prices. When a signal is generated based on our technical requirements, a security scan and metadata scan are conducted. This process ultimately produces a signal that includes all the standard data you'd expect from any other token scanner, albeit packaged in a more concise way.
Chain-agnostic...
Rogue Feature Audit (partial)
Configuration
✅ Environment variable loading
✅ Basic configuration
✅ Configuration validation
❌ Multiple environment support
✅ Secret management
❌ Configuration hot reloading
Telegram Service
✅ Bot initialization
✅ Basic message sending
✅ Error handling
❌ Command handling
❌ User interaction
❌ Message rate limiting
❌ Message formatting helpers
❌ Interactive commands
Price Service
✅ Price history tracking
✅ Active pair management
✅ Basic error handling
✅ Price aggregation
❌ Volume tracking
❌ Market depth analysis
✅ Price alert thresholds
❌ Historical data storage
Pair Lifecycle Manager
✅ Pair tracking
✅ Liquidity monitoring
✅ Basic error handling
❌ Advanced pair filtering
❌ Pair metadata tracking
❌ Historical liquidity data
⚠️ Pair scoring system
⚠️ Risk assessment
Price Analyzer
✅ Basic strategy implmentation
✅ Basic crossover detection
❌ Multiple timeframe analysis
❌ Volume analysis integration
❌ Trend strength calculation
❌ Support/Resistance detection
❌ Pattern recognition
❌ Risk management
Logging System
✅ Basic logging levels
✅ Timestamp formatting
✅ Error logging
❌ Log rotation
❌ Log persistence
❌ Performance logging
❌ Log aggregation
❌ Request/Response logging
Error Handling
✅ Basic error types
✅ Error logging
❌ Error reporting service
❌ Error aggregation
❌ Alert thresholds
❌ Error recovery strategies
❌ Circuit breakers
❌ Fallback mechanisms
