Mm2 Roblox Analytics Toolkit

# MM2 Roblox Analytics Toolkit

> Skill by [ara.so](https://ara.so) — Data Skills collection.

This toolkit provides comprehensive analytics and inventory management for Roblox's Murder Mystery 2 game. It tracks knife skins, gamepasses, win/loss ratios, and provides AI-powered strategy insights through data visualization and pattern analysis.

## Installation

### Quick Setup (Automated)

```bash
git clone https://github.com/8015238355/mm2-analytics-dashboard-2026.git
cd mm2-analytics-dashboard-2026
chmod +x setup.sh
./setup.sh --install
```

### Manual Installation

```bash
# Clone repository
git clone https://github.com/8015238355/mm2-analytics-dashboard-2026.git
cd mm2-analytics-dashboard-2026

# Install Node.js dependencies
npm install

# Install Python dependencies
python3 -m pip install -r requirements.txt
```

### Environment Configuration

Create a `.env` file in the project root:

```bash
API_OPENAI_KEY=${OPENAI_API_KEY}
API_CLAUDE_KEY=${ANTHROPIC_API_KEY}
DATA_DIRECTORY=./data/collections
ANALYTICS_INTERVAL=300
ENABLE_LIVE_TRACKING=true
ROBLOX_USER_ID=${YOUR_ROBLOX_USER_ID}
```

## Core Features

### 1. Inventory Management

Track and catalog your MM2 items including knife skins, gamepasses, and collectibles.

```python
# Python API for inventory tracking
from mm2_toolkit import InventoryManager

# Initialize inventory manager
inventory = InventoryManager(user_id=os.environ['ROBLOX_USER_ID'])

# Scan and catalog items
inventory.scan_inventory()
knife_skins = inventory.get_items(category='knife_skins', rarity='legendary')

# Export inventory data
inventory.export(format='json', output='my_inventory.json')

# Get collection statistics
stats = inventory.get_statistics()
print(f"Total items: {stats['total_count']}")
print(f"Legendary items: {stats['legendary_count']}")
print(f"Collection completion: {stats['completion_percentage']}%")
```

### 2. Analytics Dashboard

Generate gameplay statistics and performance metrics.

```python
from mm2_toolkit import AnalyticsDashboard

# Initialize analytics
dashboard = AnalyticsDashboard(profile='mystery_solver_01')

# Load gameplay data
dashboard.load_data(date_range='last_30_days')

# Generate reports
report = dashboard.generate_report(
    metrics=['win_rate', 'avg_survival_time', 'role_performance'],
    export_format='json'
)

# Visualize data
dashboard.create_visualization(
    chart_type='line',
    metric='win_rate_over_time',
    output='charts/performance.png'
)
```

### 3. Strategy Optimization

Analyze gameplay patterns and receive AI-powered recommendations.

```python
from mm2_toolkit import StrategyOptimizer

# Initialize optimizer with AI backend
optimizer = StrategyOptimizer(
    openai_key=os.environ['API_OPENAI_KEY'],
    claude_key=os.environ['API_CLAUDE_KEY']
)

# Analyze strategy patterns
patterns = optimizer.analyze_patterns(
    role='sheriff',
    game_count=50
)

# Get AI recommendations
recommendations = optimizer.get_recommendations(
    current_strategy='aggressive_sheriff',
    win_rate_target=0.75
)

for rec in recommendations:
    print(f"Strategy: {rec['name']}")
    print(f"Description: {rec['description']}")
    print(f"Expected improvement: {rec['improvement_percentage']}%")
```

## CLI Commands

### Basic Usage

```bash
# Run analytics on profile
python3 main.py --mode analytics --profile mystery_solver_01

# Export inventory
python3 main.py --mode inventory --export inventory.json --format json

# Generate strategy report
python3 main.py --mode strategy --role