game-analyzer

Parse TraitorSim game logs to analyze trust matrix evolution and voting patterns.

Updated Dec 21, 2025
One-click install
npx skills add https://github.com/rickoslyder/TraitorSim --skill game-analyzer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: game-analyzer
Source: https://github.com/rickoslyder/TraitorSim/tree/main/.claude/skills/game-analyzer
Command: npx skills add https://github.com/rickoslyder/TraitorSim --skill game-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Analyzing game logs reveals trust evolution, voting blocs, mission outcomes, and emergent behaviors that drive better design and debugging.

Core Features & Use Cases

  • Trust evolution analysis: Track updates to the trust matrix over days.
  • Voting pattern insights: Detect blocs and coordination among Traitors.
  • Emergent behavior detection: Identify unexpected alliances and strategies.

Quick Start

from src.traitorsim.analysis.game_analyzer import GameAnalyzer; analyzer = GameAnalyzer(game_log_path="data/logs/game.json"); analyzer.get_summary()

Frequently Asked Questions about game-analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze trust evolution in game logs?

Trust evolution analysis tracks how the trust matrix updates across game days, revealing shifts in player relationships and confidence. Load your game log JSON file into GameAnalyzer, then call get_summary() to extract trust changes tied to specific events and rounds.

Can I detect voting patterns and Traitor coordination from game data?

Yes. Voting pattern analysis identifies blocs and coordinated votes among players by parsing round_table_vote events from your game log. GameAnalyzer generates statistics and visualizations that expose strategic alignment and mission outcomes tied to voting behavior.

What file format do I need for game log analysis?

Game logs must be in JSON format containing event records such as trust_matrix_update, round_table_vote, and mission_result. GameAnalyzer parses these structured events to reconstruct gameplay dynamics and generate analysis summaries.

How do I identify emergent behaviors and unexpected strategies in gameplay?

Emergent behavior detection processes trust matrix evolution and voting coordination across the full game log to surface unexpected alliances and strategic patterns. Visualizations and statistical summaries from GameAnalyzer highlight deviations from expected agent behavior.

Can I use this for debugging agent behaviors and validating game design?

Yes. GameAnalyzer applies to completed games to validate agent decision-making, debug trust updates, and identify strategic patterns. Researchers and developers use the generated statistics, visualizations, and summaries to assess whether agents behave as intended.