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Agent Skill · 研究检索

architecture-design(建筑设计)

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。

architecture-design 是研究检索类 Agent Skill,可用宿主为 Local Agent,通过unknown获取,权限为调用外部服务;许可证信息还不明确,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 64,557。

总安装 297周安装 12下载 93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。
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:architecture-design(建筑设计)
来源仓库:https://smithery.ai
仓库路径:architecture-design
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

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。

architecture-design 提供界面布局与用户体验优化建议。适用于移动端或桌面端应用的原型迭代。可生成栅格系统与组件层级草案。需考虑无障碍访问基本要求。architecture-design 属于研究检索类 Skill,可作为该场景下的辅助能力补充。不替代用户测试验证可用性。

来源仓库内路径:architecture-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 Local Agent;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

    没有现成安装命令,按unknown的说明从来源页面获取,仓库路径是 architecture-design。

  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

    它需要调用外部服务,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

architecture-design 怎么安装?

公开资料没有给出可以直接复制的命令,需要按来源页面说明手动安装,仓库内路径为 architecture-design。

architecture-design 支持哪些 AI 工具?

公开资料标注支持 Local Agent。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。

architecture-design 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

architecture-design 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。

architecture-design 用的人多吗?

公开数据是累计安装 297 次,近一周安装 12 次,下载 93 次。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。

architecture-design 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 Local Agent 一种宿主,触发方式和使用习惯不用来回切换。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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 Local Agent,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

  • 需要明确授权才能用到公司项目里的场景。
  • 要求有安全扫描结论才肯安装的团队。
  • 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
architecture-design

建筑设计 · 本页

297—调用外部服务未明确未收录

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

Architecture Design

Generate professional software architecture documentation with visual diagrams and API specifications through structured interviews. Create complete ARCHITECTURE.md files covering all required sections with technology-specific patterns, C4 model diagrams, and OpenAPI 3.0 specifications.

Core Workflow

Step 1: Assess Project Type

Determine the project type by asking the user:

  • New project? Gather requirements and design architecture
  • Existing system? Document current state
  • Update needed? Identify changed components

Step 2: Gather Essential Information

Conduct a brief interview (5-7 questions maximum) to collect:

  1. Architecture pattern: Monolith, microservices, or serverless?
  2. Primary technology: Node.js, Python, Java, or other?
  3. Key components: Main services or modules?
  4. Data stores: Databases and caches?
  5. Cloud provider: AWS, GCP, Azure, or on-premise?
  6. Deployment: How is it deployed?
  7. External integrations: Third-party services?

Step 3: Select Template and Load References

Choose template based on architecture pattern:

  • Monolith → Use assets/ARCHITECTURE-monolith.md
  • Microservices → Use assets/ARCHITECTURE-microservices.md
  • Uncertain → Use assets/ARCHITECTURE.md

Load technology-specific references:

  • Node.js projects → Load references/nodejs.md for Express, NestJS, Fastify patterns
  • Python projects → Load references/python.md for Django, Flask, FastAPI patterns
  • Java projects → Load references/java.md for Spring Boot, Jakarta EE patterns

Load pattern-specific references when applicable:

  • Microservices → Load references/microservices.md for service boundaries and communication patterns
  • Serverless → Load references/serverless.md for function organization and event sources

Step 4: Generate System Diagram

Generate appropriate diagrams using scripts/generate_diagram.py:

For monolithic architectures:

python scripts/generate_diagram.py layered

For microservices architectures:

python scripts/generate_diagram.py flow

For simple systems:

python scripts/generate_diagram.py simple

Customize diagrams with JSON configuration for specific components.

Step 5: Populate Template

Complete the template sections in the specified order:

  1. Project Identification (Section 10) - Add project name, repository, contact, date
  2. Project Structure (Section 1) - Define directory layout
  3. System Diagram (Section 2) - Insert generated diagram
  4. Core Components (Section 3) - Document components from interview
  5. Data Stores (Section 4) - Describe databases and caches
  6. External Integrations (Section 5) - List third-party services
  7. Deployment (Section 6) - Detail infrastructure setup
  8. Security (Section 7) - Specify authentication and encryption
  9. Development (Section 8) - Outline setup and testing procedures
  10. Future Considerations (Section 9) - Document roadmap items
  11. Glossary (Section 11) - Define domain terminology

Apply technology-specific patterns from loaded references to enhance each section.

Step 6: Validate

Execute the validation script to ensure quality:

python scripts/validate_architecture.py ARCHITECTURE.md

Address any issues or warnings before delivering the documentation.

Interview Best Practices

Maintain focused questioning:

  • Ask 2-3 questions at a time
  • Build upon previous answers
  • Skip redundant questions

Adapt communication style:

  • Technical users: Use precise terminology
  • Non-technical users: Simplify language
  • Uncertain users: Offer defaults or placeholders

Handle information gaps:

  • Mark uncertain items for review
  • Add [TODO] for missing information
  • Suggest reasonable defaults based on context

Technology-Specific Guidance

Reference Loading Guidelines

Load references/nodejs.md for:

  • Express, NestJS, Fastify projects
  • Node.js microservices
  • Serverless Node functions

Load references/python.md for:

  • Django, Flask, FastAPI projects
  • Python microservices
  • Data pipelines and ML systems

Load references/java.md for:

  • Spring Boot applications
  • Jakarta EE systems
  • Java microservices

Load references/workflows.md for:

  • Complex interview scenarios
  • Detailed process guidance
  • Documentation update workflows

Applying Technology Patterns

After loading references, apply the patterns to enhance:

  • Project structure recommendations
  • Deployment configurations
  • Framework-specific best practices
  • Common library suggestions
  • Testing strategies and approaches

Pattern-Specific Guidance

Microservices Architecture

Load references/microservices.md and include these elements:

  • Service boundaries and responsibilities
  • Communication patterns (synchronous vs asynchronous)
  • API gateway configuration
  • Service discovery mechanism
  • Data management approach
  • Observability and monitoring setup

Use the microservices template (assets/ARCHITECTURE-microservices.md) for proper structure.

Serverless Architecture

Load references/serverless.md and include these elements:

  • Function organization and boundaries
  • Event sources and triggers
  • State management approach
  • Cold start mitigation techniques
  • Cost optimization strategies

Monolithic Architecture

Use the monolith template (assets/ARCHITECTURE-monolith.md) and emphasize:

  • Layered architecture patterns
  • Module organization principles
  • Potential future refactoring paths
  • Scaling strategy and approaches

Diagram Generation Examples

Simple Architecture Diagram

python scripts/generate_diagram.py simple '{"components": ["User", "API", "DB"], "connections": [["User", "API"], ["API", "DB"]]}'

Layered Architecture Diagram

python scripts/generate_diagram.py layered '{"Presentation": ["Web UI"], "Business": ["API"], "Data": ["PostgreSQL"]}'

Flow Architecture Diagram

python scripts/generate_diagram.py flow '[{"from": "Client", "to": "Gateway", "label": "HTTP"}, {"from": "Gateway", "to": "Service", "label": "route"}]'

C4 Context Diagram

python scripts/generate_diagram.py c4 '{"system": "E-commerce Platform", "actors": ["Customer", "Admin"], "external_systems": ["Payment Gateway", "Email Service"]}'

Integrate generated diagrams into Section 2 (System Diagram) of the ARCHITECTURE.md template.

Validation

Execute validation before delivering documentation:

python scripts/validate_architecture.py ARCHITECTURE.md

Validation checks performed:

  • Verify all 11 sections are present
  • Confirm required fields in Project Identification section
  • Ensure minimal content in each section
  • Count and report placeholder usage

Address any warnings about missing content or excessive placeholders.

Documentation Update Workflow

For incremental updates:

  1. Identify what has changed
  2. Update only affected sections
  3. Update the date in Section 10 (Project Identification)
  4. Re-run validation to ensure quality

For major updates:

  1. Review the entire document
  2. Regenerate diagrams if structure has changed
  3. Update multiple sections as needed
  4. Consider adding version notes

Mermaid Diagram Generation

After creating ARCHITECTURE.md, generate the complete set of 5 Mermaid diagrams.

Load Mermaid Instructions

When users request diagrams or complete documentation packages:

Load references/mermaid-diagrams.md

Generate Complete Diagram Set

Create all 5 diagrams following the guidance in mermaid-diagrams.md:

  1. C4 Context (Level 1) - System in its broader context
  2. C4 Container (Level 2) - Main application containers
  3. C4 Component (Level 3) - Internal component structure
  4. Data Flow - How data moves through the system
  5. C4 Deployment - Infrastructure topology and deployment

Use scripts/generate_mermaid.py with system JSON configuration.

Save diagrams as separate.mmd files:

  • 01-context.mmd
  • 02-container.mmd
  • 03-component.mmd
  • 04-dataflow.mmd
  • 05-deployment.mmd

Embed diagrams in ARCHITECTURE.md Section 2 as code blocks for easy viewing and editing.

OpenAPI Specification Generation

For systems with REST APIs, generate comprehensive OpenAPI 3.0 specifications.

Generate API Specifications

Use scripts/generate_openapi.py with appropriate parameters:

For simple CRUD operations:

python scripts/generate_openapi.py "ResourceName"

For custom API specifications:

python scripts/generate_openapi.py '{"system_name": "...", "endpoints": [...]}'

Save the generated specification as openapi.json in the project directory.

Complete Documentation Workflow

Follow this end-to-end workflow for comprehensive architecture documentation:

  1. Conduct structured interview (5-7 questions maximum)
  2. Select appropriate template and load relevant references
  3. Setup work directory: Use current working directory $(pwd)
  4. Generate ARCHITECTURE.md with all 11 sections completed
  5. Generate Mermaid diagrams (5 separate.mmd files) in work directory root
  6. Generate OpenAPI specification (if applicable) in work directory
  7. Deliver all generated artifacts to the user

Deliverable Organization

Organize generated documentation files as follows:

├── ARCHITECTURE.md              # Main architecture document
├── openapi.json                 # API specification (if applicable)
├── *.mmd (5 files)             # Mermaid diagram sources
│   ├── 01-context.mmd
│   ├── 02-container.mmd
│   ├── 03-component.mmd
│   ├── 04-dataflow.mmd
│   └── 05-deployment.mmd
└── diagrams/ (created during packaging)
    └── *.png (5 files, if rendered to images)

Example Usage

User request: "Create architecture documentation for my Node.js microservices project"

Execution approach:

  1. Select microservices template (assets/ARCHITECTURE-microservices.md)
  2. Load references/nodejs.md and references/microservices.md
  3. Conduct focused interview: services, databases, communication patterns, deployment
  4. Generate flow diagram using scripts/generate_diagram.py flow
  5. Populate all sections with Node.js and microservices-specific patterns
  6. Validate using scripts/validate_architecture.py
  7. Create comprehensive ARCHITECTURE.md in work directory

Common Usage Scenarios

New Greenfield Projects

  • Use base template (assets/ARCHITECTURE.md)
  • Focus on design decisions and architecture rationale
  • Include justification for technology choices
  • Emphasize planned architecture and future scalability

Existing System Documentation

  • Ask about current pain points and challenges
  • Document the as-is state accurately
  • Note planned improvements in Section 9 (Future Considerations)
  • Capture current technology stack and limitations

Legacy System Analysis

  • Identify undocumented or poorly understood areas
  • Mark uncertain items for further investigation
  • Suggest areas requiring clarification from stakeholders
  • Document assumptions and risks

Architecture Reviews and Updates

  • Update only sections that have changed
  • Preserve information that remains accurate
  • Add new components and relationships
  • Update date in Section 10 and note changes

Best Practices

Efficient documentation creation:

  • Begin with known information and build incrementally
  • Use placeholders for unknown items to maintain momentum
  • Leverage technology references to save time and ensure accuracy
  • Validate frequently to catch issues early

High-quality output standards:

  • Provide specific, concrete details rather than generic descriptions
  • Include actual technology stack versions and configurations
  • Use real service names, purposes, and data flows
  • Document concrete deployment infrastructure and environments

Positive user experience:

  • Avoid overwhelming users with excessive questions
  • Explain the documentation process and next steps
  • Show progress through the 11 sections clearly
  • Offer refinement and improvement after initial delivery

平台分布

Local Agent

80.73%
按下载量换算75

安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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