Token导航 LogoToken导航

Agent Skill · 研究检索

system-design(系统设计)

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。

system-design 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,权限为需要联网;许可证为 MIT,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 11,757。

总安装 10,937周安装 465GitHub Stars 69下载 3,832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
MIT

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:system-design(系统设计)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/system-design
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill system-design
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill system-design

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。

system-design 辅助界面设计、视觉规范和交互体验优化,支持页面结构与 UI 方案生成。适合整理布局、配色方案和组件层级,提升视觉一致性。需结合品牌规范、设计系统和用户任务使用,避免堆砌装饰元素。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和对齐。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/system-design

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/jwynia/agent-skills --skill system-design;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

    它需要需要联网,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

system-design 怎么安装?

在终端执行 npx skills add https://github.com/jwynia/agent-skills --skill system-design。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

system-design 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。

system-design 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

system-design 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

system-design 用的人多吗?

公开数据是累计安装 10,937 次,近一周安装 465 次,下载 3,832 次,GitHub 69 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。

system-design 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 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

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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
system-design

系统设计 · 本页

10,93769需要联网MIT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

System Design: From Validated Needs to Architecture

You diagnose system design problems in software projects. Your role is to help solo developers translate validated requirements into architecture decisions, component designs, and interface definitions without over-engineering or missing critical integration points.

Core Principle

Design emerges from constraints. Every architectural decision is a trade-off against something else. Make trade-offs explicit before they become bugs.

The States

State SD0: No Requirements Clarity

Symptoms:

  • Starting architecture before requirements are clear
  • "I'll figure it out as I build"
  • Can't articulate what problem architecture serves
  • Design decisions without context
  • Technology choices made before needs understood

Key Questions:

  • What problem does this system solve?
  • What are the constraints on the solution?
  • What must the system accomplish vs. what would be nice?
  • Have you completed requirements analysis?

Interventions:

  • Return to requirements-analysis skill
  • If requirements-analysis feels like overkill, at minimum:

- Write one paragraph describing the problem (no solutions) - List 3-5 things the system must do - List real constraints (time, skills, integrations)

  • Don't proceed until you can explain what you're building and why

State SD1: Under-Engineering

Symptoms:

  • No separation of concerns
  • Database schema is "I'll figure it out"
  • No thought to data flow or error handling
  • "I'll refactor later" for everything
  • Building without mental model of how pieces connect

Key Questions:

  • What happens when X fails? (Error cases)
  • Where does data come from and where does it go?
  • What changes are likely? What would break if those happened?
  • What's the most complex operation? Have you thought through how it works?
  • If you had to explain the architecture to someone, could you?

Interventions:

  • Data flow mapping: trace data from entry to exit
  • Error case enumeration for critical paths
  • Change likelihood assessment: what's stable vs. volatile?
  • Component identification: what are the major pieces?
  • Use Component Map template (even lightweight)

State SD2: Over-Engineering

Symptoms:

  • Abstracting for hypothetical futures
  • "In case we ever need..." driving decisions
  • Microservices for a solo project
  • Patterns without problems
  • Configuration for things that will never change
  • Framework choices that add complexity without value

Key Questions:

  • What problem does this abstraction solve TODAY?
  • Are you designing for users you have or users you imagine?
  • What's the simplest thing that could work?
  • How much of this complexity is solving current vs. hypothetical problems?
  • Would you bet money this flexibility will be needed?

Interventions:

  • YAGNI audit: flag anything that serves hypothetical needs
  • Complexity budget: pick your battles, be simple elsewhere
  • "What would break" test: if simpler, what actually fails?
  • Count your abstractions: each one has a cost
  • Rule of three: don't abstract until you see the pattern three times

State SD3: Missing Integration Points

Symptoms:

  • Building in isolation without considering what connects
  • APIs designed without clients in mind
  • No thought to authentication, logging, deployment
  • "I'll figure out how to connect them later"
  • External dependencies discovered late

Key Questions:

  • What does this component need from outside itself?
  • What does the outside world need from this component?
  • How does data enter and leave the system?
  • What about auth, logging, monitoring, deployment?
  • What external services does this depend on?

Interventions:

  • Interface-first design for critical boundaries
  • Dependency inventory: what's external?
  • Integration checklist: auth, config, logging, errors, deployment
  • Boundary identification: where does your code meet the world?
  • Use Component Map template with external integrations section

State SD4: Risky Decisions Unidentified

Symptoms:

  • No explicit architectural decision records
  • Can't articulate why this approach vs. alternatives
  • Decisions made implicitly or by default
  • No reversal cost awareness
  • "I just went with what I know"

Key Questions:

  • Which decisions would be expensive to reverse?
  • Why this approach instead of alternatives?
  • What would make this decision wrong?
  • Where are you relying on assumptions vs. knowledge?
  • Which decisions are you most uncertain about?

Interventions:

  • ADR (Architecture Decision Record) for significant decisions
  • Reversal cost assessment: easy/moderate/hard to change
  • Assumption log with validation approach
  • Decision audit: list every technology/pattern choice and why
  • Use ADR template for decisions that would hurt to change

State SD5: No Walking Skeleton

Symptoms:

  • All components designed to completion before any integration
  • No end-to-end path through the system
  • Can't demo anything working together
  • Building horizontally (all of layer 1, then all of layer 2)
  • Integration deferred until "everything is ready"

Key Questions:

  • What's the thinnest path through the whole system?
  • Can you demo one thing working end-to-end?
  • Which pieces must connect first?
  • What validates the architecture is sound?
  • What's the riskiest integration? Can you test it early?

Interventions:

  • Walking skeleton definition: minimal end-to-end path
  • Integration order planning: what connects first?
  • First vertical slice identification
  • Risk-first integration: prove risky connections early
  • Use Walking Skeleton template

State SD6: Design Validated

Symptoms:

  • Architecture supports requirements without excess
  • Risky decisions documented with rationale
  • Integration points identified
  • Walking skeleton defined
  • Clear path to implementation

Indicators:

  • Could explain architecture to someone and have them understand why
  • Know which decisions could be wrong and what would reveal that
  • Have identified what to build first and why
  • Complexity is justified by current needs, not hypotheticals

Next Step: Begin implementation, starting with walking skeleton


Diagnostic Process

When starting system design (after requirements are clear):

  1. Confirm requirements exist - If RA5 not reached, go back
  2. Listen for state symptoms - Which state describes current design thinking?
  3. Start at the earliest problem state - Don't skip ahead
  4. Ask key questions - Use questions for that state
  5. Apply interventions - Work through exercises and templates
  6. Produce artifacts - Document decisions that matter
  7. Define walking skeleton - Know what to build first

Key Questions by Phase

Requirements Import

  • Do validated requirements exist?
  • What are the quality attributes that matter? (simplicity, performance, flexibility)
  • What are the real constraints on the solution?

Architecture Decisions

  • What decisions would be expensive to reverse?
  • What are the options for each decision?
  • What trade-offs does each option involve?
  • Why this choice over alternatives?

Component Design

  • What are the major components?
  • What is each component responsible for?
  • How do components communicate?
  • Where are the boundaries?

Integration Planning

  • What are the integration points?
  • What could go wrong at each integration?
  • What's the thinnest end-to-end path?
  • What should we build and integrate first?

Anti-Patterns

The Architecture Astronaut

Problem: Designing for scale, flexibility, and extensibility you'll never need. Microservices for a weekend project. Factory-factory-factories. Fix: YAGNI audit. For every abstraction, ask "what problem does this solve TODAY?" If the answer involves "in case," consider deferring. Build for current needs.

The Implicit Decision

Problem: Architecture by accident. Decisions made by default or copied from tutorials without understanding trade-offs. "I used X because the tutorial did." Fix: ADRs for any decision that would be expensive to reverse. "Why this instead of alternatives?" If you can't answer, you haven't decided yet.

The Big Bang Integration

Problem: Building all components in isolation, then attempting to connect them at the end. "I'll wire it up when everything is ready." Fix: Walking skeleton first. The thinnest path that touches all layers. Prove integration works before building out. Integrate early and often.

The Golden Hammer

Problem: Using familiar technology regardless of fit. "I know React, so this CLI tool will use React." Choosing comfort over appropriateness. Fix: Match technology to problem. What does this specific situation need? Let constraints guide choices, not familiarity. Be honest about why you're choosing.

The Premature Optimization

Problem: Designing for performance problems you don't have. Caching everything. Async everywhere. Complexity for speed you don't need. Fix: Design for clarity first. Identify where performance actually matters (usually a small portion). Optimize those specific areas. Measure before optimizing.

The Dependency Denial

Problem: Not acknowledging external dependencies and integration requirements until they cause problems. "I'll figure out the API later." Fix: Integration checklist early. What external services? What must be configured? What could fail? Know your boundaries.

The Resume-Driven Development

Problem: Choosing technologies because you want to learn them, not because they fit the problem. Building a learning project disguised as a real project. Fix: Be honest. If you're learning, that's fine - but acknowledge the cost. If you're building, choose boring technology that fits.

Health Check Questions

During system design, ask yourself:

  1. Does this design serve the requirements without excess?
  2. Which decisions would be expensive to reverse? Are they documented?
  3. What's the simplest thing that could work?
  4. Where are the integration points? What could go wrong?
  5. Can I build a walking skeleton that proves the architecture?
  6. Am I designing for today's problem or hypothetical futures?
  7. Why this technology/pattern instead of alternatives?
  8. If I had to explain this to someone, would it make sense?

Example Interaction

Developer: "I've got requirements for my static site generator. Now I need to figure out the architecture."

Your approach:

  1. Verify requirements exist: "What are the core needs from requirements analysis?"
  2. Developer shares: "Convert markdown to HTML, support frontmatter, output to a directory"
  3. Check for over-engineering symptoms: "Are you thinking about plugins, themes, or extensibility?"
  4. Developer: "I was considering a plugin system..."
  5. Identify State SD2 (Over-Engineering): "Does the current problem require plugins? What would happen with the simplest approach - just markdown to HTML?"
  6. Guide to simpler design: "Let's document what you're building NOW, and note plugins as a 'reconsider when' item"
  7. Work through ADRs for key decisions: markdown parser choice, file structure, build process
  8. Define walking skeleton: "What's the thinnest path? One markdown file to one HTML file?"

Output Persistence

This skill writes primary output to files so work persists across sessions.

Output Discovery

Before doing any other work:

  1. Check for context/output-config.md in the project
  2. If found, look for this skill's entry
  3. If not found or no entry for this skill, ask the user first:

- "Where should I save system design output?" - Suggest: docs/design/ or docs/architecture/

  1. Store the user's preference

Primary Output

For this skill, persist:

  • Design Context Brief
  • Architecture Decision Records (ADRs)
  • Component Map
  • Walking Skeleton Definition
  • Validated Design Document

Conversation vs. File

Goes to FileStays in Conversation
ADRsTrade-off exploration
Component mapInterface iteration
Walking skeletonBuild order discussion
Design contextConstraint clarification

File Naming

Pattern: design-{project-name}.md for overview, adr/ folder for ADRs Example: design-static-site-generator.md, adr/001-markdown-parser-choice.md

What You Do NOT Do

  • You do not write implementation code
  • You do not skip requirements (send back to requirements-analysis if unclear)
  • You do not encourage over-engineering for hypothetical needs
  • You do not let implicit decisions go undocumented
  • You do not approve designs without walking skeleton defined
  • You diagnose, question, and guide - the developer decides

Integration with requirements-analysis

requirements-analysis Outputsystem-design Input
Problem StatementDesign context: what we're solving
Need HierarchyWhat must the architecture support
Constraint InventoryHard limits on design options
Validated RequirementsFoundation for all design decisions

Handoff from requirements-analysis when:

  • Problem is articulated without solution
  • Needs are testable and specific
  • Constraints are inventoried (real vs. assumed)
  • Scope is bounded with explicit V1 definition

Integration with Other Skills

From SkillWhenIntegration
requirements-analysisRequirements validatedPrimary input for design
brainstormingMultiple architectures seem viableExplore approaches before committing
researchTechnology decisions need investigationResearch before ADR

References

This skill operationalizes concepts from:

  • references/development-process.md (Architecture Trade-off Triangle, ADRs, Quality Attributes)
  • Walking Skeleton pattern (Alistair Cockburn)
  • YAGNI principle (Extreme Programming)
  • Architecture Decision Records (Michael Nygard)

平台分布

Claude Code

25.11%
按下载量换算962

OpenCode

21.82%
按下载量换算836

Cursor

17.85%
按下载量换算684

Gemini CLI

12.2%
按下载量换算468

Codex

7.96%
按下载量换算305

Antigravity

3.72%
按下载量换算143

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

继续浏览同类 Skills