Educational Solana token sniping tool with creator intelligence and rugpull detection. Provides comprehensive guidance for analyzing high-performance token detection systems, security scanning, and multi-strategy simulation.
This skill has safety concerns that you should review before use. Some patterns were detected that may pose a risk.Safety score: 60/100.
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Educational Solana token sniping tool with creator intelligence and rugpull detection capabilities. This skill provides comprehensive guidance for working with high-performance blockchain analysis, security scanning, and trading simulation systems.
This skill helps you understand and work with a hyper-efficient educational token sniping tool that:
**CRITICAL**: This is an educational tool. All trading is simulated (DRY_RUN mode is triple-locked). No real trading functionality will be created or enabled.
```
src/
├── core/ # Configuration and orchestration
├── detection/ # Blockchain monitoring and token detection
├── analysis/ # Security scanning and metrics
├── trading/ # Simulation and exit strategies
├── monitoring/ # Real-time dashboard and WebSocket
└── utils/ # Rate limiting and performance profiling
```
When examining token detection code:
```typescript
interface DetectionConfig {
sources: {
pumpfun: { enabled: true; priority: 1; multiplier: 2.0 };
raydium: { enabled: true; priority: 2; multiplier: 1.8 };
orca: { enabled: true; priority: 3; multiplier: 1.5 };
};
maxLatency: 5000;
showAllTokens: true; // Display ALL tokens with risk info
creatorIntelligence: true;
}
```
When working with security scanning:
```typescript
interface SecurityInfo {
score: number; // 0-100
visualDisplay: {
badge: '🔴' | '🟠' | '🟢';
radarChart: boolean;
tokenIcon: string;
};
creatorIntelligence: {
walletAddress: string;
rugpullHistory: { count: number; priceAtDump: number[] };
successRate: number;
riskMultiplier: number; // 1.3x verified, 1x unknown, 0.7x flagged
};
displayAllTokens: true;
}
```
When analyzing trading strategies:
```typescript
interface TradingStrategy {
simulation: {
enabledFor: 'TOKENS_UNDER_10_MINUTES';
baseAmount: 0.003; // SOL (UI configurable 0.001-0.01)
maxPositions: 500; // Auto-scaling
};
multiStrategy: {
ultraAggressive: { holdPercent: 1, stopLoss: -20 };
aggressive: { holdPercent: 15, stopLoss: -20 };
balanced: { holdPercent: 10, stopLoss: -20 };
conservative: { holdPercent: 5, stopLoss: -15 };
};
performanceBenchmarks: {
targetWinRate: 60;
targetAvgROI: 25;
maxDetectionLatency: 5000;
};
}
```
When implementing exit logic:
```typescript
interface ExitStrategy {
rugPullProtection: {
realTimeMonitoring: [
'CREATOR_WALLET_ACTIVITY',
'LIQUIDITY_REMOVAL_DETECTION',
'LARGE_HOLDER_DUMPS',
'SOCIAL_SENTIMENT_CRASH'
];
maxExitTime: 100; // 100ms emergency exit
};
creatorAwareExits: {
verifiedCreators: 'EXTENDED_HOLD';
flaggedCreators: 'QUICK_EXIT';
};
}
```
When optimizing performance:
When working with the UI:
1. **NEVER modify DRY_RUN mode** - all trading remains simulated
2. **NEVER create real trading functionality** - educational simulation only
3. **NEVER bypass safety constraints** - simulation boundaries must remain intact
4. **NEVER enable real targeting** - creator intelligence for educational analysis only
5. **ALWAYS use strict TypeScript** - no `any` types
6. **ALWAYS show ALL tokens** - never filter by security score
7. **ALWAYS respect performance benchmarks** - <5s detection, >60% win rate, >25% ROI
1. **Analyze security scanning logic**: Review honeypot detection, creator intelligence, and visual warning systems
2. **Optimize token detection**: Examine multi-source aggregation, priority weighting, and latency targets
3. **Review exit strategies**: Study multi-strategy options, rugpull protection, and creator-aware timing
4. **Performance profiling**: Monitor win rate, ROI, detection latency, and memory usage against benchmarks
5. **Creator database**: Analyze wallet tracking, rugpull history, and risk scoring systems
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