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roborracleroborracle/agent-workflow-kit/skills/system-architect/SKILL.md

system-architect

Skill0 starsChanged 3 months agoMITView on GitHub

Design scalable backend systems, APIs, databases, and infrastructure. Covers microservices, monoliths, event-driven architecture, caching strategies, and system integration patterns. Use for architectural decisions, system design, API design, or database modeling.

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    Common

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  1. Distinctive:

    Use UUIDs for distributed systems

    line 41

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Files
SKILL.md

System Architect

Design robust, scalable systems with sound architectural principles.

Architecture Decision Process

1. Requirements Gathering

  • Functional requirements
  • Non-functional requirements (performance, scale, security)
  • Constraints (budget, timeline, team skills)
  • Integration requirements
  • Compliance needs

2. Architecture Selection

PatternBest ForTrade-offs
MonolithMVPs, small teamsSimple deploy, harder to scale
MicroservicesLarge scale, multiple teamsComplex ops, better scaling
ServerlessEvent-driven, variable loadCold starts, vendor lock-in
Event-DrivenAsync workflows, decouplingComplexity, eventual consistency

API Design Principles

RESTful API Standards

Standard CRUD endpoints (GET, POST, PUT, PATCH, DELETE) with nested resources. Consistent response envelope with data, meta, and error fields.

See reference/api-patterns.md for endpoint conventions, response/error formats, status codes, pagination, and filtering.

Database Design

Schema Design Principles

  • Normalize to 3NF, denormalize for performance
  • Use UUIDs for distributed systems
  • Include audit columns (created_at, updated_at)
  • Design for query patterns
  • Plan for migrations

Index Strategy & Common Patterns

See reference/db-patterns.md for index examples (simple, composite, partial, covering), soft deletes, polymorphic associations, JSON columns, and materialized views.

Scalability Patterns

Caching Strategy

LayerToolTTLUse Case
CDNCloudflareHoursStatic assets
ApplicationRedisMinutesSession, computed
DatabaseQuery cacheSecondsFrequent queries

Event-Driven Architecture

  • Domain Events: Business occurrences (OrderPlaced)
  • Integration Events: Cross-service communication
  • Command Events: Action requests
  • Dead letter queues for failure handling
  • Retry with exponential backoff

Security Architecture

  • Authentication at API gateway
  • Authorization per endpoint
  • Input validation
  • Rate limiting
  • Encryption in transit (TLS) and at rest
  • Audit logging
  • Secrets management

Performance Targets

API and database latency targets come from rules/testing-quality.md unless the project's CLAUDE.md overrides them. Design-level targets beyond those:

Availability: 99.9%
Cache Hit Rate: > 90%

Anti-Patterns to Avoid

  • Distributed monolith
  • Chatty microservices
  • Shared database between services
  • Synchronous chains
  • Missing circuit breakers
  • Unbounded queries
  • N+1 database queries

Additional Resources

  • For detailed API design patterns (REST endpoints, response formats, status codes, pagination), see reference/api-patterns.md
  • For database design patterns (indexes, soft deletes, polymorphic associations, materialized views), see reference/db-patterns.md

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