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popup-studio-ai

enterprise

by popup-studio-ai

bkit Vibecoding Kit - PDCA methodology + Claude Code mastery for AI-native development

23🍴 10📅 Jan 24, 2026

SKILL.md


name: enterprise description: | Enterprise-grade system development with microservices, Kubernetes, and Terraform. Includes AI Native methodology and Monorepo architecture patterns. Handles high traffic, high availability, and complex architecture requirements.

Use proactively when user needs high traffic, microservices, custom infrastructure, or AI-native development patterns.

Triggers: microservices, kubernetes, terraform, k8s, AWS, monorepo, AI native, 10-day, 마이크로서비스, 모노레포, マイクロサービス, モノレポ, 微服务, 单仓库

Do NOT use for: simple websites, MVPs, or projects without infrastructure requirements. agent: infra-architect allowed-tools:

  • Read
  • Write
  • Edit
  • Glob
  • Grep
  • Bash
  • Task user-invocable: false

Advanced (Enterprise) Skill

Target Audience

  • Senior developers
  • CTOs / Architects
  • Large-scale system operators

Tech Stack

Frontend:
- Next.js 14+ (Turborepo monorepo)
- TypeScript
- Tailwind CSS
- TanStack Query
- Zustand

Backend:
- Python FastAPI (microservices)
- PostgreSQL (schema separation)
- Redis (cache, Pub/Sub)
- RabbitMQ / SQS (message queue)

Infrastructure:
- AWS (EKS, RDS, S3, CloudFront)
- Kubernetes (Kustomize)
- Terraform (IaC)
- ArgoCD (GitOps)

CI/CD:
- GitHub Actions
- Docker

Language Tier Guidance (v1.3.0)

Supported: All Tiers

Enterprise level handles complex requirements including legacy system integration.

TierUsageGuidance
Tier 1Primary servicesNew development, core features
Tier 2System/CloudGo (K8s), Rust (performance critical)
Tier 3Platform nativeiOS (Swift), Android (Kotlin), legacy Java
Tier 4Legacy integrationMigration plan required

Migration Path:

  • PHP → TypeScript (Next.js API routes)
  • Ruby → Python (FastAPI)
  • Java → Kotlin or Go

Project Structure

project/
├── apps/                        # Frontend apps (Turborepo)
│   ├── web/                    # Main web app
│   ├── admin/                  # Admin
│   └── docs/                   # Documentation site
│
├── packages/                    # Shared packages
│   ├── ui/                     # UI components
│   ├── api-client/             # API client
│   └── config/                 # Shared config
│
├── services/                    # Backend microservices
│   ├── auth/                   # Auth service
│   ├── user/                   # User service
│   ├── {domain}/               # Domain-specific services
│   └── shared/                 # Shared modules
│
├── infra/                       # Infrastructure code
│   ├── terraform/
│   │   ├── modules/            # Reusable modules
│   │   └── environments/       # Environment-specific config
│   └── k8s/
│       ├── base/               # Common manifests
│       └── overlays/           # Environment-specific patches
│
├── docs/                        # PDCA documents
│   ├── 00-requirement/
│   ├── 01-development/         # Design documents (multiple)
│   ├── 02-scenario/
│   ├── 03-refactoring/
│   └── 04-operation/
│
├── scripts/                     # Utility scripts
├── .github/workflows/           # CI/CD
├── docker-compose.yml
├── turbo.json
└── pnpm-workspace.yaml

Clean Architecture (4-Layer)

┌─────────────────────────────────────────────────────────┐
│                    API Layer                             │
│  - FastAPI routers                                       │
│  - Request/Response DTOs                                 │
│  - Auth/authz middleware                                 │
├─────────────────────────────────────────────────────────┤
│                  Application Layer                       │
│  - Service classes                                       │
│  - Use Case implementation                               │
│  - Transaction management                                │
├─────────────────────────────────────────────────────────┤
│                    Domain Layer                          │
│  - Entity classes (pure Python)                          │
│  - Repository interfaces (ABC)                           │
│  - Business rules                                        │
├─────────────────────────────────────────────────────────┤
│                 Infrastructure Layer                     │
│  - Repository implementations (SQLAlchemy)               │
│  - External API clients                                  │
│  - Cache, messaging                                      │
└─────────────────────────────────────────────────────────┘

Dependency direction: Top → Bottom
Domain Layer depends on nothing

Core Patterns

Repository Pattern

# domain/repositories/user_repository.py (interface)
from abc import ABC, abstractmethod

class UserRepository(ABC):
    @abstractmethod
    async def find_by_id(self, id: str) -> User | None:
        pass

    @abstractmethod
    async def save(self, user: User) -> User:
        pass

# infrastructure/repositories/user_repository_impl.py (implementation)
class UserRepositoryImpl(UserRepository):
    def __init__(self, db: AsyncSession):
        self.db = db

    async def find_by_id(self, id: str) -> User | None:
        result = await self.db.execute(
            select(UserModel).where(UserModel.id == id)
        )
        return result.scalar_one_or_none()

Inter-service Communication

# Synchronous (Internal API)
async def get_user_info(user_id: str) -> dict:
    async with httpx.AsyncClient() as client:
        response = await client.get(
            f"{USER_SERVICE_URL}/internal/users/{user_id}",
            headers={"X-Internal-Token": INTERNAL_TOKEN}
        )
        return response.json()

# Asynchronous (message queue)
await message_queue.publish(
    topic="user.created",
    message={"user_id": user.id, "email": user.email}
)

Terraform Module

# modules/eks/main.tf
resource "aws_eks_cluster" "this" {
  name     = "${var.environment}-${var.project_name}-eks"
  role_arn = aws_iam_role.cluster.arn
  version  = var.kubernetes_version

  vpc_config {
    subnet_ids = var.subnet_ids
  }

  tags = merge(var.tags, {
    Environment = var.environment
  })
}

Kubernetes Deployment

# k8s/base/backend/deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: user-service
spec:
  replicas: 2
  template:
    spec:
      containers:
        - name: user-service
          image: ${ECR_REGISTRY}/user-service:${TAG}
          resources:
            requests:
              cpu: "100m"
              memory: "256Mi"
            limits:
              cpu: "500m"
              memory: "512Mi"
          livenessProbe:
            httpGet:
              path: /health
              port: 8000

Environment Configuration

EnvironmentInfrastructureDeployment Method
LocalDocker ComposeManual
StagingEKSArgoCD Auto Sync
ProductionEKSArgoCD Manual Sync

Security Rules

✅ Allowed
- Retrieve secrets from Secrets Manager
- IAM role-based access
- VPC internal communication
- mTLS (inter-service)

❌ Prohibited
- Hardcoded secrets
- DB in public subnet
- Using root account
- Excessive IAM permissions

CI/CD Pipeline

Push to feature/*
    ↓
GitHub Actions (CI)
    - Lint
    - Test
    - Build Docker image
    - Push to ECR
    ↓
PR to staging
    ↓
ArgoCD Auto Sync (Staging)
    ↓
PR to main
    ↓
ArgoCD Manual Sync (Production)

SoR Priority

1st Priority: Codebase
  - scripts/init-db.sql (source of truth for DB schema)
  - services/{service}/app/ (each service implementation)

2nd Priority: CLAUDE.md / Convention docs
  - services/CLAUDE.md
  - frontend/CLAUDE.md
  - infra/CLAUDE.md

3rd Priority: docs/ design documents
  - For understanding design intent
  - If different from code, code is correct

AI Native Development

3 Core Principles

  1. Document-First Design: Write design docs BEFORE code
  2. Monorepo Context Control: All code in one repo for AI context
  3. PR-Based Collaboration: Every change through PR

10-Day Development Pattern

DayFocusOutput
1ArchitectureMarket analysis + System architecture
2-3CoreAuth, User + Business services
4-5UXPO feedback → Documentation → Implementation
6-7QAZero Script QA + bug fixes
8InfraTerraform + GitOps
9-10ProductionSecurity review + Deployment

Monorepo Benefits for AI

Mono-repo:
└─ project/
    ├─ frontend/ ──────┐
    ├─ services/ ──────┤  AI reads completely
    ├─ infra/ ─────────┤  Context unified
    └─ packages/ ──────┘

✅ AI understands full context
✅ Single source of truth for types
✅ Atomic commits across layers
✅ Consistent patterns enforced

CLAUDE.md Hierarchy

project/
├── CLAUDE.md           # Project-wide context
├── frontend/CLAUDE.md  # Frontend conventions
├── services/CLAUDE.md  # Backend conventions
└── infra/CLAUDE.md     # Infra conventions

Rule: Area-specific CLAUDE.md overrides project-level rules

Score

Total Score

70/100

Based on repository quality metrics

SKILL.md

SKILL.mdファイルが含まれている

+20
LICENSE

ライセンスが設定されている

+10
説明文

100文字以上の説明がある

0/10
人気

GitHub Stars 100以上

0/15
最近の活動

1ヶ月以内に更新

+10
フォーク

10回以上フォークされている

+5
Issue管理

オープンIssueが50未満

+5
言語

プログラミング言語が設定されている

+5
タグ

1つ以上のタグが設定されている

+5

Reviews

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