Scale Game
GitHub一种架构评估方法，通过在极端规模（如10亿用户或毫秒级）下测试系统，暴露正常尺度下隐藏的根本性缺陷与限制。
Trigger Scenarios
Install
npx skills add mrgoonie/claudekit-skills --skill Scale Game -g -y
SKILL.md
Frontmatter
{
"name": "Scale Game",
"version": "1.1.0",
"description": "Test at extremes (1000x bigger\/smaller, instant\/year-long) to expose fundamental truths hidden at normal scales",
"when_to_use": "when uncertain about scalability, edge cases unclear, or validating architecture for production volumes"
}
Scale Game
Overview
Test your approach at extreme scales to find what breaks and what surprisingly survives.
Core principle: Extremes expose fundamental truths hidden at normal scales.
Quick Reference
| Scale Dimension | Test At Extremes | What It Reveals |
|---|---|---|
| Volume | 1 item vs 1B items | Algorithmic complexity limits |
| Speed | Instant vs 1 year | Async requirements, caching needs |
| Users | 1 user vs 1B users | Concurrency issues, resource limits |
| Duration | Milliseconds vs years | Memory leaks, state growth |
| Failure rate | Never fails vs always fails | Error handling adequacy |
Process
- Pick dimension - What could vary extremely?
- Test minimum - What if this was 1000x smaller/faster/fewer?
- Test maximum - What if this was 1000x bigger/slower/more?
- Note what breaks - Where do limits appear?
- Note what survives - What's fundamentally sound?
Examples
Example 1: Error Handling
Normal scale: "Handle errors when they occur" works fine At 1B scale: Error volume overwhelms logging, crashes system Reveals: Need to make errors impossible (type systems) or expect them (chaos engineering)
Example 2: Synchronous APIs
Normal scale: Direct function calls work At global scale: Network latency makes synchronous calls unusable Reveals: Async/messaging becomes survival requirement, not optimization
Example 3: In-Memory State
Normal duration: Works for hours/days At years: Memory grows unbounded, eventual crash Reveals: Need persistence or periodic cleanup, can't rely on memory
Red Flags You Need This
- "It works in dev" (but will it work in production?)
- No idea where limits are
- "Should scale fine" (without testing)
- Surprised by production behavior
Remember
- Extremes reveal fundamentals
- What works at one scale fails at another
- Test both directions (bigger AND smaller)
- Use insights to validate architecture early
Version History
- 80113d8 Current 2026-08-20 08:14
