# Openclaw Senior Architect

> Senior Architect

- Skill: `urjuyaimon09/openclaw-senior-architect` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add urjuyaimon09/openclaw-senior-architect`
- Raw SKILL.md: https://api.skillmd.com/api/skills/urjuyaimon09/openclaw-senior-architect/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: urjuyaimon09 (https://skillmd.com/u/urjuyaimon09)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/urjuyaimon09/openclaw-senior-architect

---

Senior Architect

Architecture design and analysis tools for making informed technical decisions.

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

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Analyzes project dependencies for coupling, circular dependencies, and outdated packages.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

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 --help for usage information
Check reference documentation for detailed patterns and workflows
Use --verbose flag for detailed explanations and recommendations