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backend-development

Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(12)

  • SKILL.md4.4 KB
  • references/backend-api-design.md10.4 KB
  • references/backend-architecture.md12.2 KB
  • references/backend-authentication.md9.2 KB
  • references/backend-code-quality.md12.8 KB
  • references/backend-debugging.md18.5 KB
  • references/backend-devops.md10.5 KB
  • references/backend-mindset.md11.0 KB
  • references/backend-performance.md9.4 KB
  • references/backend-security.md7.9 KB
  • references/backend-technologies.md7.5 KB
  • references/backend-testing.md10.4 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Backend Development Skill

Production-ready backend development with modern technologies, best practices, and proven patterns.

When to Use

  • Designing RESTful, GraphQL, or gRPC APIs
  • Building authentication/authorization systems
  • Optimizing database queries and schemas
  • Implementing caching and performance optimization
  • OWASP Top 10 security mitigation
  • Designing scalable microservices
  • Testing strategies (unit, integration, E2E)
  • CI/CD pipelines and deployment
  • Monitoring and debugging production systems

Technology Selection Guide

Languages: Node.js/TypeScript (full-stack), Python (data/ML), Go (concurrency), Rust (performance) Frameworks: NestJS, FastAPI, Django, Express, Gin Databases: PostgreSQL (ACID), MongoDB (flexible schema), Redis (caching) APIs: REST (simple), GraphQL (flexible), gRPC (performance)

See: references/backend-technologies.md for detailed comparisons

Reference Navigation

Core Technologies:

  • backend-technologies.md - Languages, frameworks, databases, message queues, ORMs
  • backend-api-design.md - REST, GraphQL, gRPC patterns and best practices

Security & Authentication:

  • backend-security.md - OWASP Top 10 2025, security best practices, input validation
  • backend-authentication.md - OAuth 2.1, JWT, RBAC, MFA, session management

Performance & Architecture:

  • backend-performance.md - Caching, query optimization, load balancing, scaling
  • backend-architecture.md - Microservices, event-driven, CQRS, saga patterns

Quality & Operations:

  • backend-testing.md - Testing strategies, frameworks, tools, CI/CD testing
  • backend-code-quality.md - SOLID principles, design patterns, clean code
  • backend-devops.md - Docker, Kubernetes, deployment strategies, monitoring
  • backend-debugging.md - Debugging strategies, profiling, logging, production debugging
  • backend-mindset.md - Problem-solving, architectural thinking, collaboration

Key Best Practices (2025)

Security: Argon2id passwords, parameterized queries (98% SQL injection reduction), OAuth 2.1 + PKCE, rate limiting, security headers

Performance: Redis caching (90% DB load reduction), database indexing (30% I/O reduction), CDN (50%+ latency cut), connection pooling

Testing: 70-20-10 pyramid (unit-integration-E2E), Vitest 50% faster than Jest, contract testing for microservices, 83% migrations fail without tests

DevOps: Blue-green/canary deployments, feature flags (90% fewer failures), Kubernetes 84% adoption, Prometheus/Grafana monitoring, OpenTelemetry tracing

Quick Decision Matrix

NeedChoose
Fast developmentNode.js + NestJS
Data/ML integrationPython + FastAPI
High concurrencyGo + Gin
Max performanceRust + Axum
ACID transactionsPostgreSQL
Flexible schemaMongoDB
CachingRedis
Internal servicesgRPC
Public APIsGraphQL/REST
Real-time eventsKafka

Implementation Checklist

API: Choose style → Design schema → Validate input → Add auth → Rate limiting → Documentation → Error handling

Database: Choose DB → Design schema → Create indexes → Connection pooling → Migration strategy → Backup/restore → Test performance

Security: OWASP Top 10 → Parameterized queries → OAuth 2.1 + JWT → Security headers → Rate limiting → Input validation → Argon2id passwords

Testing: Unit 70% → Integration 20% → E2E 10% → Load tests → Migration tests → Contract tests (microservices)

Deployment: Docker → CI/CD → Blue-green/canary → Feature flags → Monitoring → Logging → Health checks

Resources

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같은 저장소의 스킬

2d-games

무료

2D game development principles. Sprites, tilemaps, physics, camera.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

3d-games

무료

3D game development principles. Rendering, shaders, physics, cameras.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

aesthetic

무료

Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

VoDaiLocz/kilo-kit-mcp282026년 9월 13일 업데이트

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