Skip to content
FunCoding

Search

Search docs, Skills and MCP

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.

代码质量与审查1.4kskills/designing-architecture/SKILL.md

Install

Send this to Claude Code, Codex or Cursor. The agent checks the Skill for safety first and installs it only after you confirm.

读取 https://funcoding.ai/skills/cloudai-x/claude-workflow-v2/designing-architecture/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

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

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:

## 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.

Similar Skills

claude-api
anthropics/skills180k

claude-api

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

Code quality & review

ponytail-review
DietrichGebert/ponytail158k

ponytail-review

Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected code, not only the diff. Each finding is explained in plain English. Use for "review this", "code review", "review the last commit", "review my PR", "is this over-engineered", /ponytail-review.

Code quality & review

code-review-and-quality
addyosmani/agent-skills103k

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.

Code quality & review

documentation-and-adrs
addyosmani/agent-skills103k

documentation-and-adrs

Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

Code quality & review

code-simplification
addyosmani/agent-skills103k

code-simplification

Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.

Code quality & review

understand
Egonex-AI/Understand-Anything86k

understand

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

Code quality & review