Token导航 LogoToken导航TokenDH.com
研究检索external-serviceunknown未标认证来源可访问许可证需确认审计未展示

architecture-design建筑设计

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。

总安装

297

周安装

12

下载量

93
Local Agent

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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。

简介

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。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

external-service

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills