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from mm2_analytics import AnalyticsEngine, Profile, InventoryManager

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from mm2_analytics import InventoryManager, TradeAnalyzer

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from mm2_analytics import StrategyAnalyzer, GameSession

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from mm2_analytics import Dashboard, ChartGenerator

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{
  "analytics": {
    "metrics": {
      "win_rate": {
        "enabled": true,
        "calculation": "wins / (wins + losses)",
        "time_ranges": ["7d", "30d", "all"]
      },
      "inventory_value": {
        "enabled": true,
        "currency": "robux",
        "update_frequency": 3600
      },
      "role_performance": {
        "enabled": true,
        "roles": ["sheriff", "murderer", "innocent"],
        "metrics": ["accuracy", "survival_time", "win_rate"]
      }
    },
    "export": {
      "auto_export": true,
      "formats": ["json", "csv"],
      "destination": "./data/exports/",
      "compression": "gzip"
    }
  }
}

from mm2_analytics import DailyAnalyzer
from datetime import datetime

def daily_analytics_routine(profile_name):
    """Run daily analytics and generate report"""
    analyzer = DailyAnalyzer(profile=profile_name)
    
    # Sync latest data
    print("Syncing inventory...")
    analyzer.sync_inventory()
    
    # Calculate daily metrics
    print("Calculating metrics...")
    metrics = analyzer.calculate_daily_metrics()
    
    # Generate report
    report = analyzer.generate_report(
        date=datetime.now().strftime("%Y-%m-%d"),
        include_charts=True,
        export_format="pdf"
    )
    
    # Send notifications if milestones reached
    if metrics.has_milestones():
        analyzer.notify_milestones(metrics.milestones)
    
    return report

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from mm2_analytics import InventoryOptimizer

def optimize_inventory(profile):
    """Optimize inventory for maximum value"""
    optimizer = InventoryOptimizer(profile=profile)
    
    # Get current inventory state
    current_inventory = optimizer.get_current_state()
    
    # Identify duplicate items
    duplicates = optimizer.find_duplicates()
    print(f"Found {len(duplicates)} duplicate items")
    
    # Get trade recommendations
    trades = optimizer.recommend_trades(
        strategy="maximize_value",
        min_profit_margin=0.15,
        risk_level="low"
    )
    
    # Calculate portfolio diversity
    diversity_score = optimizer.calculate_diversity()
    print(f"Portfolio diversity: {diversity_score:.2%}")
    
    return {
        "duplicates": duplicates,
        "recommended_trades": trades,
        "diversity_score": diversity_score
    }

from mm2_analytics import AIStrategyAssistant
import os

def get_strategy_suggestions(profile, role):
    """Get AI-powered gameplay suggestions"""
    assistant = AIStrategyAssistant(
        openai_key=os.getenv("API_OPENAI_KEY"),
        claude_key=os.getenv("API_CLAUDE_KEY")
    )
    
    # Analyze recent performance
    recent_games = assistant.load_recent_games(profile, limit=50)
    performance = assistant.analyze_performance(recent_games, role=role)
    
    # Generate suggestions
    suggestions = assistant.generate_suggestions(
        performance_data=performance,
        role=role,
        improvement_areas=["map_awareness", "timing", "positioning"]
    )
    
    # Rank by expected impact
    ranked_suggestions = assistant.rank_by_impact(suggestions)
    
    return ranked_suggestions

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from mm2_analytics import InventoryManager, SyncError

try:
    manager = InventoryManager(profile="MysterySolver2026")
    inventory = manager.sync_from_roblox()
except SyncError as e:
    print(f"Sync failed: {e}")
    
    # Retry with fallback mode
    inventory = manager.sync_from_roblox(
        fallback_mode=True,
        use_cache=True,
        timeout=60
    )
    
    # Verify sync integrity
    if manager.verify_sync():
        print("Sync completed with cached data")
    else:
        print("Manual sync required - check Roblox connection")

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from mm2_analytics import PerformanceOptimizer

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from mm2_analytics import RateLimiter
import time

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from mm2_analytics import Pipeline, Processor

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from mm2_analytics import LiveMonitor
import asyncio

async def monitor_gameplay():
    """Monitor live gameplay sessions"""
    monitor = LiveMonitor(profile="mystery_solver_01")
    
    await monitor.connect()
    
    async for event in monitor.stream_events():
        if event.type == "game_start":
            print(f"Game started - Role: {event.role}")
        elif event.type == "game_end":
            print(f"Game ended - Result: {event.result}")
            # Update analytics
            await monitor.update_stats(event.data)
        elif event.type == "inventory_change":
            print(f"New item acquired: {event.item}")

This skill provides comprehensive coverage of the MM2 Analytics Dashboard for AI coding agents to effectively assist developers in inventory tracking, analytics, and gameplay optimization for Murder Mystery 2 on Roblox.