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design-interview-methodology设计面试方法

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

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CodexClaudeCursorGemini CLI

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GitHub

来源数

2

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unknown

最后核验

2026-05-01

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来源可访问

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通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:design-interview-methodology(设计面试方法)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/design-interview-methodology
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill design-interview-methodology
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

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复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/melodic-software/claude-code-plugins --skill design-interview-methodology

简介

提供系统设计的结构化框架,适用于面试准备与架构讨论。

  • 涵盖白板设计、技术面试与教学场景,包含四个关键步骤。
  • 使用时需明确目标时长(通常45-60分钟)并分配各环节时间。
  • 安装方式:GitHub,命令为 npx skills add https://github.com/melodic-software/claude-code-plugins --skill design-interview-methodology。
  • 注意:重点在于方法论指导而非具体答案,需用户自行填充细节。

SKILL.md

Design Interview Methodology

This skill provides a structured framework for approaching system design interviews and architectural discussions.

When to Use This Skill

Keywords: system design interview, whiteboard design, architecture discussion, technical interview, design framework

Use this skill when:

  • Preparing for a system design interview
  • Structuring a whiteboard architectural session
  • Teaching others how to approach design problems
  • Practicing with design exercises
  • Leading architectural discussions with stakeholders

The 4-Step Framework

System design interviews typically last 45-60 minutes. This framework ensures you cover all bases while demonstrating structured thinking.

StepTimePurpose
1. Requirements5-10 minClarify scope, constraints, scale
2. High-Level Design10-15 minDraw major components and data flow
3. Deep Dive15-20 minDetail 1-2 critical components
4. Wrap-Up5-10 minTrade-offs, bottlenecks, improvements

Step 1: Requirements Gathering (5-10 minutes)

Goal: Understand what to build and constraints before designing.

Functional Requirements

Ask about core functionality:

  • "What are the primary use cases?"
  • "What should users be able to do?"
  • "What are the must-have vs. nice-to-have features?"

Non-Functional Requirements (NFRs)

Clarify quality attributes:

CategoryQuestions to Ask
ScaleHow many users? DAU/MAU? Read/write ratio?
PerformanceLatency requirements? Throughput targets?
AvailabilityUptime requirements? (99.9% = 8.76 hours downtime/year)
ConsistencyStrong or eventual consistency?
DurabilityData loss tolerance? Backup requirements?

Back-of-Envelope Estimation

Quick calculations to inform design:

Example: Design a URL shortener

Users: 100M monthly active
Writes: 100M URLs/month = ~40 writes/second
Reads: 10:1 ratio = 400 reads/second
Storage: 100M * 500 bytes = 50GB/month = 600GB/year

Detailed estimation techniques: See estimation-techniques skill.

Requirements Checklist

Before proceeding to design:

  • Core use cases identified
  • Scale understood (users, data, requests)
  • Read/write ratio known
  • Latency/throughput targets set
  • Consistency requirements clear
  • Availability targets established

Step 2: High-Level Design (10-15 minutes)

Goal: Draw the major components and show data flow.

Start with the Obvious

Begin with the simplest architecture that could work:

Client --> API Gateway --> Service --> Database

Then add complexity as needed based on requirements.

Core Components to Consider

ComponentWhen to Include
Load BalancerMultiple servers, horizontal scaling
API GatewayAuthentication, rate limiting, routing
CDNStatic content, global users
CacheRead-heavy, latency-sensitive
Message QueueAsync processing, decoupling
DatabasePersistent storage (SQL vs NoSQL decision)
SearchFull-text search, complex queries
Object StorageLarge files, media content

Data Flow Narration

Walk through the system explaining each step:

"When a user creates a short URL:
1. Request hits the load balancer
2. API Gateway validates the request and checks rate limits
3. Service generates a unique short code
4. Short code and URL are stored in the database
5. Cache is updated for fast reads
6. Response returns the shortened URL"

API Design

Sketch key API endpoints:

POST /urls          - Create short URL
GET  /{shortCode}   - Redirect to long URL
GET  /urls/{id}/stats - Get click analytics

Database Schema Sketch

Show key tables/collections:

URLs table:
- id: primary key
- short_code: indexed, unique
- long_url: original URL
- user_id: foreign key
- created_at: timestamp
- expires_at: nullable timestamp

Step 3: Deep Dive (15-20 minutes)

Goal: Demonstrate depth on 1-2 critical components.

How to Choose What to Deep Dive

Let the interviewer guide, or choose based on:

  1. Most complex component - Shows technical depth
  2. Most critical for requirements - Shows understanding
  3. Your strength area - Play to your expertise

Common Deep Dive Topics

TopicWhat to Cover
Database scalingSharding strategy, replication, indexes
CachingCache strategy, invalidation, hit ratio
Data consistencyConflict resolution, distributed transactions
SearchIndexing, ranking, query optimization
MessagingDelivery guarantees, ordering, dead letters
Rate limitingAlgorithm choice, distributed implementation

Example Deep Dive: URL Shortener ID Generation

Option 1: Auto-increment
  Pros: Simple, guaranteed unique
  Cons: Predictable, single point of failure, hard to scale

Option 2: UUID
  Pros: No coordination needed
  Cons: Too long (36 chars), not URL-friendly

Option 3: Base62 encoding of counter
  Pros: Short, URL-friendly
  Cons: Requires coordination for distributed systems

Option 4: Pre-generated IDs
  Pros: Fast, no runtime coordination
  Cons: ID exhaustion, more complex

Recommendation: Pre-generated ID ranges + Base62 encoding
- Each server gets a range of IDs
- IDs are Base62 encoded for short URLs
- Handles distributed scale without coordination per request

Quantify Trade-offs

Always explain trade-offs with specifics:

  • "This adds latency of ~5ms but improves reliability from 99% to 99.9%"
  • "This uses 3x more storage but reduces query time from 100ms to 10ms"
  • "This increases complexity but allows horizontal scaling to 10x traffic"

Step 4: Wrap-Up (5-10 minutes)

Goal: Summarize, identify issues, and propose improvements.

Identify Bottlenecks

Where will the system break first as scale increases?

"The main bottleneck is the database. At 10x current scale:
- Write throughput becomes limiting
- Solution: Implement sharding by URL prefix
- Fallback: Read replicas for analytics queries"

Discuss Trade-offs Made

Summarize key decisions and alternatives:

"We chose eventual consistency for the redirect cache:
- Benefit: Lower latency, simpler architecture
- Cost: Up to 5 seconds of stale data possible
- Alternative: Strong consistency with higher latency"

Propose Improvements

If you had more time, what would you add?

ImprovementBenefit
Analytics pipelineUsage insights, business value
Abuse detectionMalware/spam URL protection
Geographic distributionLower latency globally
A/B testing capabilityFeature experimentation

Handle Edge Cases

Mention edge cases you'd address:

  • What if the database is down?
  • What if a URL expires mid-redirect?
  • What if a malicious user spams URL creation?
  • What about duplicate long URLs?

Common Pitfalls to Avoid

1. Jumping to Solution

Problem: Starting to design without understanding requirements. Fix: Spend 5-10 minutes on requirements first.

2. Over-Engineering

Problem: Adding every component you know. Fix: Start simple, add complexity only when justified by requirements.

3. Not Quantifying

Problem: Vague statements like "it's fast" or "it scales." Fix: Use numbers: "handles 10K requests/second with p99 latency of 50ms."

4. Ignoring Trade-offs

Problem: Presenting only benefits of your design. Fix: Actively discuss what you're sacrificing for each decision.

5. Silent Designing

Problem: Drawing without explaining. Fix: Narrate your thought process constantly.

Interview Signals: What Interviewers Look For

Strong Signals

  • Asks clarifying questions before designing
  • Starts with requirements, not solutions
  • Quantifies scale with back-of-envelope math
  • Explains trade-offs for each decision
  • Identifies bottlenecks proactively
  • Acknowledges what they don't know

Red Flags

  • Jumps to favorite technology without justification
  • Ignores scale/performance requirements
  • Can't explain why a component is needed
  • No consideration of failure scenarios
  • Unable to identify trade-offs
  • Defensive when challenged

Time Management Tips

SituationResponse
Running short on timeSkip to wrap-up, summarize trade-offs
Interviewer redirectsFollow their lead, they're guiding you
Stuck on a componentAcknowledge, move on, come back if time
Asked unknown technologyExplain your reasoning, ask about constraints

Practice Strategy

Before the Interview

  1. Study common design problems (see design-problem-catalog skill - Phase 4)
  2. Practice back-of-envelope calculations (see estimation-techniques skill)
  3. Know your quality attributes (see quality-attributes-taxonomy skill)
  4. Time yourself on practice problems

During Practice

  • Set a 45-minute timer
  • Practice on a whiteboard or paper (not IDE)
  • Narrate your thoughts out loud
  • Record yourself and review

Related Skills

  • estimation-techniques - Back-of-envelope calculations for scale
  • quality-attributes-taxonomy - NFRs and the "-ilities"
  • cap-theorem - Consistency/availability trade-offs (Phase 2)
  • design-problem-catalog - Common interview problems (Phase 4)

Related Commands

  • /sd:design <problem> - Interactive design session (Phase 4)
  • /sd:estimate <scenario> - Capacity calculations
  • /sd:explain <concept> - Explain any concept

Related Agents

  • system-design-interviewer - Mock interview practice (Phase 4)
  • capacity-planner - Back-of-envelope calculations
  • architecture-critic - Challenge your designs (Phase 4)

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101

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