match3-difficulty-reviewer

Analyze match-3 level difficulty by cognitive load and early choice density.

Updated Jan 26, 2026
One-click install
npx skills add https://github.com/hoonzinope/skills --skill match3-difficulty-reviewer
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: match3-difficulty-reviewer
Source: https://github.com/hoonzinope/skills/tree/main/game-skill/match3-difficulty-reviewer
Command: npx skills add https://github.com/hoonzinope/skills --skill match3-difficulty-reviewer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This skill decomposes match-3 level difficulty by cognitive load and early decision density, then clearly explains failure reasons and documents the findings to a designated .documents/game file.

Core Features & Use Cases

  • Cognitive-load and early-choice density analysis for match-3 levels.
  • Clear failure-clarity explanations with actionable recommendations.
  • Generates a MATCH3_DIFFICULTY_REVIEW.md scaffold using the provided templates and checklist, written to .documents/game/.

Quick Start

Review a match-3 level to identify difficulty drivers and generate a MATCH3_DIFFICULTY_REVIEW.md scaffold in .documents/game.

Frequently Asked Questions about match3-difficulty-reviewer

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

FAQPage Schema
How do I review match-3 level difficulty and balance for cognitive load?

Match-3 level difficulty review analyzes cognitive load and early decision density to identify difficulty drivers. It evaluates level structure, game modes, and edge cases, then generates a difficulty review document with actionable balance and pacing recommendations.

How do I audit match-3 game pacing using early choice density?

Match-3 pacing audit evaluates early choice density to determine how initial board configurations drive player decision-making. It assesses cognitive load by analyzing available moves at level start, generating structured feedback on pacing adjustments.

What is failure clarity in match-3 game design and how do I evaluate it?

Failure clarity in match-3 game design measures how clearly a player understands why they lost a level. Difficulty review evaluates this by analyzing level mechanics, board constraints, and game mode rules, then documents findings on whether failure conditions are communicated effectively.

Can I use this match-3 difficulty analysis for different game modes and edge cases?

Match-3 difficulty analysis applies to typical match-3 levels across common game modes and edge cases. It evaluates cognitive load and choice density patterns specific to each mode, providing tailored balance and feedback guidance for varied level configurations.

How do I generate a structured difficulty review document for match-3 levels?

Generate a structured difficulty review by scaffolding a MATCH3_DIFFICULTY_REVIEW.md file from a provided template and checklist. The output is written to .documents/game/ and contains documented findings on cognitive load, failure clarity, and balance recommendations.

What's the best way to identify difficulty drivers in match-3 level design?

The best way to identify match-3 difficulty drivers is decomposing levels by cognitive load and early decision density. This approach isolates which mechanics and board setups create excessive player strain, then maps those findings to specific balance and feedback adjustments.