// Real-time chaos injection endpoint
const chaosFactors = await fetch('/api/local-news')
  .then(res => res.json())
  .then(data => ({
    politicalTurbulence: data.coupRumors * 0.3,
    infrastructureFails: data.powerOutages * 0.15,
    socialMediaPanic: data.trendingHashtags.length * 0.05,
    uncleInfluence: data.familyNetworkStrength * 0.25,
    vibeCheck: analyzeMemeQuality(data.latestMemes)
  }));

// Feed into AlgoForge risk calculator
const adjustedDSCR = baseDSCR * (1 - chaosFactors.total);
const confidenceLevel = calculateVibes(chaosFactors.vibeCheck);

// Generate human-readable output
if (confidenceLevel < 0.3) {
  console.log("🚨 Time to convert everything to USD and hide it under mattress");
}

# Alternative Python implementation for the data scientists
import requests
import pandas as pd
from chaos_engine import LocalRiskModel

class YourCountryRiskEngine:
    def __init__(self, country_code, uncle_influence=0.5):
        self.country = country_code
        self.uncle_factor = uncle_influence
        self.model = LocalRiskModel(exclude_western_bias=True)
    
    def calculate_real_risk(self, investment_data):
        # Get street-level intelligence
        street_intel = self.scrape_group_chats()
        generator_status = self.check_neighbor_generator()
        
        # Apply the Uncle Adjustment™
        risk_score = self.model.calculate(investment_data)
        adjusted_score = risk_score * (1 - self.uncle_factor)
        
        return {
            'risk': adjusted_score,
            'confidence': street_intel['confidence'],
            'recommendation': self.generate_advice(),
            'backup_plan': 'Always have a backup plan'
        }