资深架构师
senior-architect
by alirezarezvani
适合系统设计评审、ADR记录和扩展性规划,分析依赖与耦合,权衡单体或微服务、数据库与技术栈选型,并输出Mermaid、PlantUML、ASCII架构图。
搞系统设计、技术选型和扩展规划时,用它能更快理清架构决策与依赖关系,还能直接产出 Mermaid/PlantUML 图,方案讨论效率很高。
安装
claude skill add --url github.com/alirezarezvani/claude-skills/tree/main/engineering-team/senior-architect文档
Senior Architect
Architecture design and analysis tools for making informed technical decisions.
Table of Contents
- Quick Start
- Tools Overview
- Decision Workflows
- 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
Tools Overview
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 relationshipslayer- 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Analyzes project dependencies for coupling, circular dependencies, and outdated packages.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- Outdated packages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
| Characteristic | Points to SQL | Points to NoSQL |
|---|---|---|
| Structured with relationships | ✓ | |
| ACID transactions required | ✓ | |
| Flexible/evolving schema | ✓ | |
| Document-oriented data | ✓ | |
| Time-series data | ✓ (specialized) |
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
| Team Size | Recommended Starting Point |
|---|---|
| 1-3 developers | Modular monolith |
| 4-10 developers | Modular monolith or service-oriented |
| 10+ developers | Consider microservices |
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
| Requirement | Recommended Pattern |
|---|---|
| Rapid MVP development | Modular Monolith |
| Independent team deployment | Microservices |
| Complex domain logic | Domain-Driven Design |
| High read/write ratio difference | CQRS |
| Audit trail required | Event Sourcing |
| Third-party integrations | Hexagonal/Ports & Adapters |
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:
- A module has significantly different scaling needs
- A team needs independent deployment
- Technology constraints require separation
Reference Documentation
Load these files for detailed information:
| File | Contains | Load when user asks about |
|---|---|---|
references/architecture_patterns.md | 9 architecture patterns with trade-offs, code examples, and when to use | "which pattern?", "microservices vs monolith", "event-driven", "CQRS" |
references/system_design_workflows.md | 6 step-by-step workflows for system design tasks | "how to design?", "capacity planning", "API design", "migration" |
references/tech_decision_guide.md | Decision matrices for technology choices | "which database?", "which framework?", "which cloud?", "which cache?" |
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
Getting Help
- Run any script with
--helpfor usage information - Check reference documentation for detailed patterns and workflows
- Use
--verboseflag for detailed explanations and recommendations
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