Senior Architect

Senior Architect

Architecture design and analysis tools for making informed technical decisions.

Overview

Use this skill for architecture reviews, technology choices, dependency analysis, and system diagrams when the user needs a decision backed by trade-offs.

When to Use

• Designing or reviewing system architecture
• Comparing architectural patterns or deployment models
• Choosing databases, infrastructure, or integration boundaries
• Generating diagrams or dependency reports for an existing codebase

Table of Contents

• Quick Start
• Tools Overview
  • Architecture Diagram Generator
  • Dependency Analyzer
  • Project Architect
• Decision Workflows
  • Database Selection
  • Architecture Pattern Selection
  • Monolith vs Microservices
• Reference Documentation
• Tech Stack Coverage
• Common Commands

Quick Start

# Generate architecture diagram from project
python scripts/architecture_diagram_generator.py ./my-project --format mermaid

# Analyze dependencies for issues
python scripts/dependency_analyzer.py ./my-project --output json

# Get architecture assessment
python scripts/project_architect.py ./my-project --verbose

Quick Reference

1. Architecture Diagram Generator

Generates architecture diagrams from project structure in multiple formats.

Solves: "I need to visualize my system architecture for documentation or team discussion"

Input: Project directory path Output: Diagram code (Mermaid, PlantUML, or ASCII)

Supported diagram types:

• component - Shows modules and their relationships
• layer - Shows architectural layers (presentation, business, data)
• deployment - Shows deployment topology

Usage:

# Mermaid format (default)
python scripts/architecture_diagram_generator.py ./project --format mermaid --type component

# PlantUML format
python scripts/architecture_diagram_generator.py ./project --format plantuml --type layer

# ASCII format (terminal-friendly)
python scripts/architecture_diagram_generator.py ./project --format ascii

# Save to file
python scripts/architecture_diagram_generator.py ./project -o architecture.md

Example output (Mermaid):

graph TD
    A[API Gateway] --> B[Auth Service]
    A --> C[User Service]
    B --> D[(PostgreSQL)]
    C --> D

2. Dependency Analyzer

Analyzes project dependencies for coupling, circular dependencies, and outdated packages.

Solves: "I need to understand my dependency tree and identify potential issues"

Input: Project directory path Output: Analysis report (JSON or human-readable)

Analyzes:

• Dependency tree (direct and transitive)
• Circular dependencies between modules
• Coupling score (0-100)
• Outdated packages

Supported package managers:

• npm/yarn (package.json)
• Python (requirements.txt, pyproject.toml)
• Go (go.mod)
• Rust (Cargo.toml)

Usage:

# Human-readable report
python scripts/dependency_analyzer.py ./project

# JSON output for CI/CD integration
python scripts/dependency_analyzer.py ./project --output json

# Check only for circular dependencies
python scripts/dependency_analyzer.py ./project --check circular

# Verbose mode with recommendations
python scripts/dependency_analyzer.py ./project --verbose

Example output:

Dependency Analysis Report
==========================
Total dependencies: 47 (32 direct, 15 transitive)
Coupling score: 72/100 (moderate)

Issues found:
- CIRCULAR: auth → user → permissions → auth
- OUTDATED: lodash 4.17.15 → 4.17.21 (security)

Recommendations:
1. Extract shared interface to break circular dependency
2. Update lodash to fix CVE-2020-8203

3. Project Architect

Analyzes project structure and detects architectural patterns, code smells, and improvement opportunities.

Solves: "I want to understand the current architecture and identify areas for improvement"

Input: Project directory path Output: Architecture assessment report

Detects:

• Architectural patterns (MVC, layered, hexagonal, microservices indicators)
• Code organization issues (god classes, mixed concerns)
• Layer violations
• Missing architectural components

Usage:

# Full assessment
python scripts/project_architect.py ./project

# Verbose with detailed recommendations
python scripts/project_architect.py ./project --verbose

# JSON output
python scripts/project_architect.py ./project --output json

# Check specific aspect
python scripts/project_architect.py ./project --check layers

Example output:

Architecture Assessment
=======================
Detected pattern: Layered Architecture (confidence: 85%)

Structure analysis:
  ✓ controllers/  - Presentation layer detected
  ✓ services/     - Business logic layer detected
  ✓ repositories/ - Data access layer detected
  ⚠ models/       - Mixed domain and DTOs

Issues:
- LARGE FILE: UserService.ts (1,847 lines) - consider splitting
- MIXED CONCERNS: PaymentController contains business logic

Recommendations:
1. Split UserService into focused services
2. Move business logic from controllers to services
3. Separate domain models from DTOs

Decision Workflows

Database Selection Workflow

Use when choosing a database for a new project or migrating existing data.

Step 1: Identify data characteristics

Step 2: Evaluate scale requirements

• <1M records, single region → PostgreSQL or MySQL
• 1M-100M records, read-heavy → PostgreSQL with read replicas

• 100M records, global distribution → CockroachDB, Spanner, or DynamoDB

• High write throughput (>10K/sec) → Cassandra or ScyllaDB

Step 3: Check consistency requirements

• Strong consistency required → SQL or CockroachDB
• Eventual consistency acceptable → DynamoDB, Cassandra, MongoDB

Step 4: Document decision Create an ADR (Architecture Decision Record) with:

• Context and requirements
• Options considered
• Decision and rationale
• Trade-offs accepted

Quick reference:

PostgreSQL → Default choice for most applications
MongoDB    → Document store, flexible schema
Redis      → Caching, sessions, real-time features
DynamoDB   → Serverless, auto-scaling, AWS-native
TimescaleDB → Time-series data with SQL interface

Architecture Pattern Selection Workflow

Use when designing a new system or refactoring existing architecture.

Step 1: Assess team and project size

Step 2: Evaluate deployment requirements

• Single deployment unit acceptable → Monolith
• Independent scaling needed → Microservices
• Mixed (some services scale differently) → Hybrid

Step 3: Consider data boundaries

• Shared database acceptable → Monolith or modular monolith
• Strict data isolation required → Microservices with separate DBs
• Event-driven communication fits → Event-sourcing/CQRS

Step 4: Match pattern to requirements

See references/architecture_patterns.md for detailed pattern descriptions.

Monolith vs Microservices Decision

Choose Monolith when:

• Team is small (<10 developers)
• Domain boundaries are unclear
• Rapid iteration is priority
• Operational complexity must be minimized
• Shared database is acceptable

Choose Microservices when:

• Teams can own services end-to-end
• Independent deployment is critical
• Different scaling requirements per component
• Technology diversity is needed
• Domain boundaries are well understood

Hybrid approach: Start with a modular monolith. Extract services only when:

1. A module has significantly different scaling needs
2. A team needs independent deployment
3. Technology constraints require separation

References

Load these files for detailed information:

Tech Stack Coverage

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin, Rust Frontend: React, Next.js, Vue, Angular, React Native, Flutter Backend: Node.js, Express, FastAPI, Go, GraphQL, REST Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, Cassandra Infrastructure: Docker, Kubernetes, Terraform, AWS, GCP, Azure CI/CD: GitHub Actions, GitLab CI, CircleCI, Jenkins

Common Commands

# Architecture visualization
python scripts/architecture_diagram_generator.py . --format mermaid
python scripts/architecture_diagram_generator.py . --format plantuml
python scripts/architecture_diagram_generator.py . --format ascii

# Dependency analysis
python scripts/dependency_analyzer.py . --verbose
python scripts/dependency_analyzer.py . --check circular
python scripts/dependency_analyzer.py . --output json

# Architecture assessment
python scripts/project_architect.py . --verbose
python scripts/project_architect.py . --check layers
python scripts/project_architect.py . --output json

Troubleshooting

1. Run any script with --help for usage information
2. Check reference documentation for detailed patterns and workflows
3. Use --verbose flag for detailed explanations and recommendations