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dragonked2 / backend-dev

Comprehensive backend development methodology covering API design, authentication, database design, caching, testing, deployment, and monitoring. Full lifecycle from requirements through production.

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SKILL.md
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Backend Development Skill Suite

Overview

This skill provides a complete backend development methodology following the full lifecycle:

Requirements → Architecture → Implementation → Testing → Deployment → Monitoring

When to Use

  • Building RESTful or GraphQL APIs
  • Designing microservices or monolithic backends
  • Implementing authentication/authorization systems
  • Database schema design and optimization
  • Caching strategy implementation
  • API security hardening
  • Production deployment and monitoring

Lifecycle Phases

Phase 1: Requirements & Architecture

  1. Define API contract first — Write OpenAPI/Swagger spec before code
  2. Choose technology stack — Match to team expertise and project needs
  3. Design data model — ERD before implementation
  4. Plan authentication — JWT, OAuth2, sessions based on use case
  5. Identify integration points — Third-party APIs, message queues, caches

Phase 2: Implementation

  1. Project structure — Follow language-specific conventions
  2. Error handling — Structured errors from day one
  3. Validation — Input validation at API boundary
  4. Logging — Structured, correlation IDs, log levels
  5. Security — Auth middleware, rate limiting, CORS, input sanitization

Phase 3: Testing

  1. Unit tests — Business logic, utilities, helpers
  2. Integration tests — API endpoints, database operations
  3. Contract tests — API spec compliance
  4. Load tests — Performance baseline
  5. Security tests — OWASP Top 10 checklist

Phase 4: Deployment

  1. Docker — Multi-stage builds, minimal images
  2. CI/CD — Automated testing, linting, building
  3. Configuration — Environment variables, secrets management
  4. Health checks — Liveness and readiness probes
  5. Graceful shutdown — Handle SIGTERM, drain connections

Phase 5: Monitoring

  1. Metrics — Request rate, error rate, latency (RED method)
  2. Logging — Centralized, searchable, structured
  3. Tracing — Distributed tracing across services
  4. Alerting — On error spikes, latency degradation
  5. Dashboards — Operational visibility

Core Principles

  • Defense in depth — Never trust a single layer
  • Fail fast, fail safe — Validate early, handle errors gracefully
  • Observability by default — Log, trace, and measure everything
  • Stateless where possible — Horizontal scalability
  • Security is not optional — Every endpoint must be secured

Technology Sub-Skills

Select the appropriate sub-skill based on your stack:

Sub-SkillWhen to Use
nodejsNode.js projects with Express, Fastify, or NestJS
pythonPython projects with FastAPI, Django, or Flask
rustRust projects with Axum, Actix-web, or Rocket
databaseDatabase schema, queries, optimization (any stack)
authAuthentication and authorization (any stack)
cachingCaching strategies (any stack)

Checklist

  • [ ] API contract defined (OpenAPI spec)
  • [ ] Authentication strategy chosen and implemented
  • [ ] Database schema designed and migrated
  • [ ] Input validation on all endpoints
  • [ ] Error handling with proper HTTP status codes
  • [ ] Rate limiting implemented
  • [ ] Structured logging with correlation IDs
  • [ ] Health check endpoint
  • [ ] Graceful shutdown handling
  • [ ] Unit and integration tests written
  • [ ] Docker build working
  • [ ] CI/CD pipeline configured
  • [ ] Monitoring and alerting in place