Is this skill only for large-scale enterprise systems?

No, testing at both the maximum and minimum extremes (e.g., zero data or instant execution) reveals logic errors and edge cases applicable to any software project.

What dimensions does the Scale Game skill test?

It evaluates systems based on volume (items), speed (latency), users (concurrency), duration (uptime), and failure rates.

How does this skill help with production readiness?

It forces the AI to consider scenarios like massive concurrency or year-long uptime, exposing issues like race conditions and memory leaks that typically don't appear in development environments.

Can I use this for API design and optimization?

Yes, it is excellent for determining if an API should be synchronous or asynchronous by analyzing behavior under high network latency or massive user volume.

What is the Scale Game in Claude Code?

It is a specialized problem-solving methodology that tests software designs at extreme scales (e.g., 1000x larger or smaller) to reveal hidden architectural flaws and fundamental limits.

Scale Game: Extreme Stress-Testing

Name: Scale Game: Extreme Stress-Testing
Author: rafaelcalleja

byrafaelcalleja

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보안 및 테스팅

Identifies architectural weaknesses and hidden bottlenecks by stress-testing software concepts at extreme theoretical scales.

소개

The Scale Game skill empowers Claude to evaluate software designs by pushing variables to their absolute limits—from one billion concurrent users to millisecond execution times. By simulating these extremes, the skill helps developers uncover fundamental truths about their architecture, expose memory leaks, identify concurrency issues, and validate production readiness before writing a single line of code. It transforms vague scaling assumptions into concrete requirements for asynchronous processing, persistent storage, and robust error handling.

주요 기능

Architectural validation for high-volume production environments
Minimum and maximum extreme testing methodology
Multi-dimensional scale analysis across volume, speed, and duration
1 GitHub stars
Identification of algorithmic complexity and resource limits
Concurrency and race condition bottleneck discovery

사용 사례

Validating if a new feature's data model can scale from 10 to 10 million records
Determining if a synchronous API needs to be redesigned as an asynchronous messaging system
Testing the long-term stability of in-memory state management over years of uptime

소개

주요 기능

Architectural validation for high-volume production environments
Minimum and maximum extreme testing methodology
Multi-dimensional scale analysis across volume, speed, and duration
1 GitHub stars
Identification of algorithmic complexity and resource limits
Concurrency and race condition bottleneck discovery

사용 사례

Validating if a new feature's data model can scale from 10 to 10 million records
Determining if a synchronous API needs to be redesigned as an asynchronous messaging system
Testing the long-term stability of in-memory state management over years of uptime