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Adversarial intelligence — behavioral detection, whale tracking, sentiment analysis
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Based on SOC occupation classification
S+ Grade Universal Trading Skill Pack for AI Agents. Trinity Architecture: Inference → Signal → Execution → Self-Upgrade. S+ Additions: Vectorized Backtest Engine, Web3 DEX Executor, LLM Agent Tool Adapter, CI/CD, 57 tests, >90% core coverage.
Web3 DEX execution layer — MEV protection, gas optimization, on-chain swaps
Technical signal generators — OBI, Funding Arbitrage, Kelly Criterion
| name | adversarial |
| version | 2.0.0 |
| description | Adversarial intelligence — behavioral detection, whale tracking, sentiment analysis |
| author | VelonLabs |
| skills | [{"name":"fomo_detector","class":"FOMODetector","module":"skills.adversarial.sentiment","description":"Fear-Of-Missing-Out and panic regime detection","triggers":["fomo","panic","greed","sentiment","behavioral"]},{"name":"whale_tracker","class":"WhaleTracker","module":"skills.adversarial.whale","description":"On-chain whale transaction classification","triggers":["whale","onchain","accumulation","distribution"]}] |
| dependencies | [] |
Detects FOMO and panic regimes from price/volume dynamics.
from skills.adversarial.sentiment import FOMODetector
fomo = FOMODetector()
result = fomo.detect(
symbol="BTC/USDT",
prices=[50000, 52000, 55000, 58000],
volumes=[100, 500, 2000, 8000],
)
Classifies whale transactions as accumulation, distribution, or neutral.
from skills.adversarial.whale import WhaleTracker
whale = WhaleTracker(etherscan_api_key="your_key")
cls = whale.classify_whale_transaction(
from_addr="0x...",
to_addr="0x...",
value_eth=1500.0,
)