game-designer

ohadf2015's avatarfrom ohadf2015

Analyze game mechanics, propose features, and research competitors to improve LexiClash engagement and virality.

⭐0stars🔀0forks📁View on GitHub🕐Updated Jan 11, 2026
[Brand and Creative Direction]

When & Why to Use This Skill

The Game Designer skill is a specialized tool designed to enhance game engagement and virality through rigorous mechanics analysis and competitor research. By utilizing frameworks like Bartle’s Player Types and a multi-dimensional rating system (Fun, Retention, Virality, and Effort), it helps developers propose high-impact features and optimize social sharing loops to drive organic growth.

Use Cases

  • Competitive Benchmarking: Researching industry leaders like Wordle and Scrabble GO to identify underserved player needs and market opportunities.
  • Feature Design & Evaluation: Proposing new game mechanics tailored to specific player personas (Achievers, Explorers, Socializers) and scoring them based on retention impact.
  • Virality Optimization: Designing social proof elements and 'share triggers,' such as milestone celebrations and challenge links, to improve the viral coefficient.
  • Psychological Validation: Analyzing game loops to ensure they create flow states and build long-term player habits through achievement systems and leaderboards.
namegame-designer
descriptionAnalyze game mechanics, propose features, and research competitors to improve LexiClash engagement and virality.
allowed-toolsRead, Write, Edit, Grep, Glob, WebSearch, mcp__memory__*

Game Designer Skill

Design features for LexiClash, a real-time multiplayer word game with neo-brutalist aesthetics.

Memory Integration

Before Starting

Recall past game design decisions and feature analysis:

mcp__memory__memory_recall(query="game design feature [feature-area] mechanic")

After Completing

Store game design decisions and analysis:

mcp__memory__memory_store(
  content="Game design: [feature-name] - [description]. Target players: [player-types]. Impact: Fun=[x], Retention=[x], Viral=[x]. Decision: [approved/rejected] because [reason].",
  type="fact",
  tags=["game-design", "feature", "[feature-area]"],
  importance=7
)

For competitor insights:

mcp__memory__memory_store(
  content="Competitor insight: [competitor] - [mechanic/feature]. What works: [analysis]. Applicable to LexiClash: [yes/no/maybe] because [reason].",
  type="fact",
  tags=["game-design", "competitor", "[competitor-name]"],
  importance=6
)

LexiClash Core

Mechanics: 5x5-9x9 boards, 8-sec combos (2.25x), rarity scoring, fire rounds (2x) Modes: Multiplayer, Single-Player, Daily challenges Features: 30+ achievements, 100-level XP, global leaderboards, streaks, emoji shares Tech: Next.js + React + Socket.IO + Supabase (5 languages)

Feature Analysis Framework

Player Types (Bartle)

  • Achievers: progression, unlocks
  • Explorers: discovery, rare words
  • Socializers: sharing, connection
  • Killers: competition, leaderboards

Rate Each Feature

  • Fun Factor (1-10)
  • Retention Impact (1-10)
  • Viral Coefficient (0-2)
  • Implementation Effort (S/M/L/XL)

What to Do

  1. Research competitors - Search Wordle, Word Hunt, Scrabble GO, Words With Friends patterns
  2. Identify opportunities - Underserved player types? Broken loops? Viral potential?
  3. Propose features - Must fit neo-brutalist aesthetic, work across 5 languages
  4. Validate psychology - Creates flow state? Triggers sharing? Builds habits?
  5. Design for virality - What's the share trigger? Social proof element? Network effect?

Quick Wins (High Impact, Low Effort)

  • Enhanced share cards with stats
  • "Beat my score" challenge links
  • Achievement showcase
  • Streak milestone celebrations

Core Features (Medium Effort)

  • Friend system with challenges
  • Weekly tournaments
  • Theme variations
  • Custom room settings

Evaluation Checklist

  • Enhances word-finding?
  • Works across all 5 languages?
  • No pay-to-win?
  • Fits neo-brutalist aesthetic?
  • Has success metrics?
  • Creates sharing opportunities?

References