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Agent Skill · 研究检索

design-interview-methodology(设计面试方法)

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。

design-interview-methodology 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 70,176。

总安装 212周安装 9GitHub Stars 61下载 74核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

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。

命令行安装

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

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

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。

来源仓库内路径:skills/design-interview-methodology

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/melodic-software/claude-code-plugins --skill d…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

design-interview-methodology 怎么安装?

在终端执行 npx skills add https://github.com/melodic-software/claude-code-plugins --skill design-inte…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

design-interview-methodology 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

design-interview-methodology 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

design-interview-methodology 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

design-interview-methodology 用的人多吗?

公开数据是累计安装 212 次,近一周安装 9 次,下载 74 次,GitHub 61 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

design-interview-methodology 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
design-interview-methodology

设计面试方法 · 本页

21261接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

平台分布

Codex

36.2%
按下载量换算27

Claude

29.81%
按下载量换算22

Cursor

18.45%
按下载量换算14

Gemini CLI

9.65%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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