What dimensions does the Scale Game test?

It focuses on five primary dimensions: Volume (items), Speed (latency), Users (concurrency), Duration (state growth), and Failure Rate.

What is the Scale Game principle?

It is a mental framework that involves testing a system at extremes (1,000x larger or smaller) to reveal fundamental truths and failure points that are hidden at normal operating scales.

How does it help with error handling?

It simulates high failure rates to determine if your current logging and recovery strategies will overwhelm the system or crash under extreme production stress.

When should I use the Scale Game skill?

Apply this skill when you are uncertain about production scalability, when edge cases are unclear, or when you need to validate a new architecture before deployment.

Does this skill perform actual automated load tests?

No, this skill provides specialized guidance and patterns for Claude to help you analytically reason through scale-related challenges during the design and coding phase.

Scale Game Problem Solving

Name: Scale Game Problem Solving
Author: GGPrompts

byGGPrompts

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安全与测试

Validates architectural decisions by simulating extreme scaling scenarios to identify hidden bottlenecks and system failures.

关于

The Scale Game skill enhances Claude's problem-solving capabilities by stress-testing software concepts at extreme magnitudes. By analyzing how systems behave when components are 1,000x larger, smaller, faster, or slower, it uncovers fundamental design flaws, concurrency issues, and scalability limits that are often invisible at standard development scales. This proactive approach helps developers validate production readiness and refine architectures early in the development lifecycle.

主要功能

Analytical frameworks for evaluating failure rates and state growth
Identification of hidden algorithmic complexity limits
2 GitHub stars
Stress testing for concurrency and resource management
Extreme scaling simulations across five critical dimensions
Architecture validation for production-grade reliability

使用场景

Validating if a local database schema can handle 1 billion records
Testing if synchronous API logic will fail under global network latency
Evaluating memory state growth for services intended to run for years

关于

主要功能

Analytical frameworks for evaluating failure rates and state growth
Identification of hidden algorithmic complexity limits
2 GitHub stars
Stress testing for concurrency and resource management
Extreme scaling simulations across five critical dimensions
Architecture validation for production-grade reliability

使用场景

Validating if a local database schema can handle 1 billion records
Testing if synchronous API logic will fail under global network latency
Evaluating memory state growth for services intended to run for years