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Designing Architecture

CommunityPopular
CloudAI-X
designing-architecture

Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.

Overview

PublisherCloudAI-X
Repositoryclaude-workflow-v2
Skill namedesigning-architecture
Stars
1.4K
Forks
188
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by CloudAI-X on GitHub. Read the source before you install it.

Installation

Install the Designing Architecture AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/CloudAI-X/claude-workflow-v2.git /tmp/claude-workflow-v2
mkdir -p .claude/skills
cp -r /tmp/claude-workflow-v2/skills/designing-architecture .claude/skills/designing-architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Designing Architecture in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Designing Architecture on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Designing Architecture is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Designing Architecture

When to Load

  • Trigger: System design, module structure, new project scaffolding, choosing architecture patterns
  • Skip: Simple bug fixes or minor code changes that don't affect architecture

Architecture Decision Workflow

Copy this checklist and track progress:

Architecture Design Progress:
- [ ] Step 1: Understand requirements and constraints
- [ ] Step 2: Assess project size and team capabilities
- [ ] Step 3: Select architecture pattern
- [ ] Step 4: Define directory structure
- [ ] Step 5: Document trade-offs and decision
- [ ] Step 6: Validate against decision framework

Pattern Selection Guide

By Project Size

SizeRecommended Pattern
Small (<10K LOC)Simple MVC/Layered
Medium (10K-100K)Clean Architecture
Large (>100K)Modular Monolith or Microservices

By Team Size

TeamRecommended
1-3 devsMonolith with clear modules
4-10 devsModular Monolith
10+ devsMicroservices (if justified)

Common Patterns

1. Layered Architecture

┌─────────────────────────────┐
│       Presentation          │  ← UI, API Controllers
├─────────────────────────────┤
│       Application           │  ← Use Cases, Services
├─────────────────────────────┤
│         Domain              │  ← Business Logic, Entities
├─────────────────────────────┤
│      Infrastructure         │  ← Database, External APIs
└─────────────────────────────┘

Use when: Simple CRUD apps, small teams, quick prototypes

2. Clean Architecture

┌─────────────────────────────────────┐
│            Frameworks & Drivers      │
│  ┌─────────────────────────────┐    │
│  │     Interface Adapters       │    │
│  │  ┌─────────────────────┐    │    │
│  │  │   Application       │    │    │
│  │  │  ┌─────────────┐    │    │    │
│  │  │  │   Domain    │    │    │    │
│  │  │  └─────────────┘    │    │    │
│  │  └─────────────────────┘    │    │
│  └─────────────────────────────┘    │
└─────────────────────────────────────┘

Use when: Complex business logic, long-lived projects, testability is key

3. Hexagonal (Ports & Adapters)

        ┌──────────┐
        │ HTTP API │
        └────┬─────┘
             │ Port
    ┌────────▼────────┐
    │                 │
    │   Application   │
    │     Core        │
    │                 │
    └────────┬────────┘
             │ Port
        ┌────▼─────┐
        │ Database │
        └──────────┘

Use when: Need to swap external dependencies, multiple entry points

4. Event-Driven Architecture

Producer → Event Bus → Consumer
              ├─→ Consumer
              └─→ Consumer

Use when: Loose coupling needed, async processing, scalability

5. CQRS (Command Query Responsibility Segregation)

┌─────────────┐      ┌─────────────┐
│  Commands   │      │   Queries   │
│  (Write)    │      │   (Read)    │
└──────┬──────┘      └──────┬──────┘
       │                    │
       ▼                    ▼
  Write Model          Read Model
       │                    │
       └────────┬───────────┘
           Event Store

Use when: Different read/write scaling, complex domains, event sourcing

Directory Structure Patterns

Feature-Based (Recommended for medium+)

src/
├── features/
│   ├── users/
│   │   ├── api/
│   │   ├── components/
│   │   ├── hooks/
│   │   ├── services/
│   │   └── types/
│   └── orders/
│       ├── api/
│       ├── components/
│       └── ...
├── shared/
│   ├── components/
│   ├── hooks/
│   └── utils/
└── app/
    └── ...

Layer-Based (Simple apps)

src/
├── controllers/
├── services/
├── models/
├── repositories/
└── utils/

Decision Framework

When making architectural decisions, evaluate against these criteria:

  1. Simplicity - Start simple, evolve when needed
  2. Team Skills - Match architecture to team capabilities
  3. Requirements - Let business needs drive decisions
  4. Scalability - Consider growth trajectory
  5. Maintainability - Optimize for change

Trade-off Analysis Template

Use this template to document architectural decisions:

markdown
## Decision: [What we're deciding]

### Context

[Why this decision is needed now]

### Options Considered

1. Option A: [Description]
2. Option B: [Description]

### Trade-offs

| Criteria         | Option A | Option B |
| ---------------- | -------- | -------- |
| Complexity       | Low      | High     |
| Scalability      | Medium   | High     |
| Team familiarity | High     | Low      |

### Decision

We chose [Option] because [reasoning].

### Consequences

- [What this enables]
- [What this constrains]

Validation Checklist

After selecting an architecture, validate against:

Architecture Validation:
- [ ] Matches project size and complexity
- [ ] Aligns with team skills and experience
- [ ] Supports current requirements
- [ ] Allows for anticipated growth
- [ ] Dependencies flow inward (core has no external deps)
- [ ] Clear boundaries between modules/layers
- [ ] Testing strategy is feasible
- [ ] Trade-offs are documented

If validation fails, reconsider the pattern selection or adjust the implementation approach.

Frequently asked questions

What does the Designing Architecture AI skill do?

Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.

Why use Designing Architecture on TypingMind?

Because you install it once and use it with any model. Designing Architecture is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Designing Architecture in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CloudAI-X/claude-workflow-v2/tree/main/skills/designing-architecture. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Designing Architecture?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Designing Architecture?

As many as you like. As long as a model supports skills, you can use Designing Architecture with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Designing Architecture AI skill free?

Yes. It is published on GitHub by CloudAI-X under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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