system-architect
System architecture skill for designing scalable, maintainable software systems. Covers microservices/monolith decisions, API design, DB selection, caching, security, and scalability planning.
Best use case
system-architect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
System architecture skill for designing scalable, maintainable software systems. Covers microservices/monolith decisions, API design, DB selection, caching, security, and scalability planning.
Teams using system-architect should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/system-architect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How system-architect Compares
| Feature / Agent | system-architect | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
System architecture skill for designing scalable, maintainable software systems. Covers microservices/monolith decisions, API design, DB selection, caching, security, and scalability planning.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# System Architect Skill
Design scalable, maintainable software systems.
## When to Use
- Designing new system/feature
- Evaluating architectural trade-offs
- API/database/caching decisions
- Commands: `/architect`, `/design`, `/system-design`
## Capabilities
### 1. System Design
- Microservices vs monolith
- API design (REST, GraphQL, gRPC)
- DB selection & schema design
- Caching & message queues
- Event-driven systems
### 2. Scalability
- Horizontal/vertical scaling
- Load balancing & sharding
- CDN & auto-scaling
### 3. Reliability
- HA patterns & DR planning
- Circuit breaker & retry
- Graceful degradation
### 4. Security
- Auth systems (OAuth, JWT, SSO)
- Authorization (RBAC, ABAC)
- API security & encryption
## Architecture Decision Process
### Step 1: Requirements
```markdown
1. Functional: Core features, workflows, integrations
2. Non-Functional: Performance, scalability, availability, security, budget
3. Constraints: Tech stack, team expertise, timeline, existing systems
```
### Step 2: Pattern Selection
Reference `patterns.json` for patterns, tech recommendations, trade-offs.
### Step 3: Design Doc Template
```markdown
# Architecture Design Document
## 1. Overview
[High-level description]
## 2. Goals & Non-Goals
## 3. Architecture
### System Diagram
### Components
| Component | Responsibility | Technology |
|-----------|---------------|------------|
### Data Flow
## 4. Technical Decisions
### Decision 1: [Title]
- Context | Options | Decision | Rationale
## 5. API Design
## 6. Data Model
## 7. Security
## 8. Scalability
## 9. Monitoring & Observability
## 10. Risks & Mitigations
```
## Pattern Reference
### Communication
| Pattern | Use When | Trade-offs |
|---------|----------|------------|
| Sync REST | Simple CRUD | Tight coupling |
| Async Queue | Decoupling | Complexity |
| Event Sourcing | Audit trail | Storage |
| CQRS | Read/write opt | Eventual consistency |
| GraphQL | Flexible queries | Caching |
| gRPC | High perf | Browser support |
### Data
| Pattern | Use When | Trade-offs |
|---------|----------|------------|
| SQL | ACID, complex queries | Scaling |
| NoSQL | Flexibility, scale | Consistency |
| Cache-aside | Read-heavy | Invalidation |
### Resilience
| Pattern | Purpose |
|---------|---------|
| Circuit Breaker | Prevent cascade failures |
| Retry w/ Backoff | Handle transient failures |
| Bulkhead | Isolate failures |
| Timeout | Prevent hanging |
| Fallback | Graceful degradation |
## Project Structures
Reference `structures.json` for:
- Python: FastAPI, Django
- TypeScript: Next.js, React, Express
- Java: Spring Boot
- Go: Standard Layout
## Tech Stack Recommendations
### Web Apps
```
Frontend: React/Next.js, Vue/Nuxt, Angular
Backend: Node.js, Go, Python (FastAPI), Rust
DB: PostgreSQL, MongoDB
Cache: Redis | Queue: RabbitMQ, SQS, Kafka
Search: Elasticsearch, Meilisearch
```
### Real-time
```
WebSocket: Socket.io, ws
Pub/Sub: Redis, Kafka
```
### Data-Intensive
```
Processing: Spark, Flink
Storage: S3, GCS
Warehouse: Snowflake, BigQuery
Pipeline: Airflow, Dagster
```
## Diagramming
### ASCII Component
```
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ Client │────▶│ API Gateway │────▶│ Services │
└─────────────┘ └─────────────┘ └─────────────┘
│ │
▼ ▼
┌─────────────┐ ┌─────────────┐
│ Auth │ │ Database │
└─────────────┘ └─────────────┘
```
### Mermaid Sequence
```mermaid
sequenceDiagram
Client->>API: Request
API->>Auth: Validate Token
Auth-->>API: Valid
API->>Service: Process
Service->>DB: Query
DB-->>Service: Data
Service-->>API: Response
API-->>Client: Response
```
## Evaluation Criteria
| Criterion | Weight | Description |
|-----------|--------|-------------|
| Scalability | High | Can it handle growth? |
| Maintainability | High | Easy to modify/debug? |
| Performance | Med-High | Meets latency/throughput? |
| Cost | Medium | Infra + dev cost |
| Security | High | Meets requirements? |
| Complexity | Medium | Team can build/operate? |
## Output Templates
### Quick Decision
```markdown
**Question**: [What needs deciding]
**Recommendation**: [Approach]
**Rationale**: [Why]
**Trade-offs**: [Accepting]
**Alternatives**: [Other options]
```
## Integration
- **code-reviewer**: Validate impl matches design
- **postgres-mcp**: DB schema design
- **jira-bridge**: Create impl ticketsRelated Skills
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