senior-architect
Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin, Flutter, Postgres, GraphQL, Go, Python. I...
Best use case
senior-architect is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin, Flutter, Postgres, GraphQL, Go, Python. I...
Teams using senior-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/senior-architect/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How senior-architect Compares
| Feature / Agent | senior-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?
Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin, Flutter, Postgres, GraphQL, Go, Python. I...
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
# Senior Architect Complete toolkit for senior architect with modern tools and best practices. ## Quick Start ### Main Capabilities This skill provides three core capabilities through automated scripts: ```bash # Script 1: Architecture Diagram Generator python scripts/architecture_diagram_generator.py [options] # Script 2: Project Architect python scripts/project_architect.py [options] # Script 3: Dependency Analyzer python scripts/dependency_analyzer.py [options] ``` ## Core Capabilities ### 1. Architecture Diagram Generator Automated tool for architecture diagram generator tasks. **Features:** - Automated scaffolding - Best practices built-in - Configurable templates - Quality checks **Usage:** ```bash python scripts/architecture_diagram_generator.py <project-path> [options] ``` ### 2. Project Architect Comprehensive analysis and optimization tool. **Features:** - Deep analysis - Performance metrics - Recommendations - Automated fixes **Usage:** ```bash python scripts/project_architect.py <target-path> [--verbose] ``` ### 3. Dependency Analyzer Advanced tooling for specialized tasks. **Features:** - Expert-level automation - Custom configurations - Integration ready - Production-grade output **Usage:** ```bash python scripts/dependency_analyzer.py [arguments] [options] ``` ## Reference Documentation ### Architecture Patterns Comprehensive guide available in `references/architecture_patterns.md`: - Detailed patterns and practices - Code examples - Best practices - Anti-patterns to avoid - Real-world scenarios ### System Design Workflows Complete workflow documentation in `references/system_design_workflows.md`: - Step-by-step processes - Optimization strategies - Tool integrations - Performance tuning - Troubleshooting guide ### Tech Decision Guide Technical reference guide in `references/tech_decision_guide.md`: - Technology stack details - Configuration examples - Integration patterns - Security considerations - Scalability guidelines ## Tech Stack **Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin **Frontend:** React, Next.js, React Native, Flutter **Backend:** Node.js, Express, GraphQL, REST APIs **Database:** PostgreSQL, Prisma, NeonDB, Supabase **DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI **Cloud:** AWS, GCP, Azure ## Development Workflow ### 1. Setup and Configuration ```bash # Install dependencies npm install # or pip install -r requirements.txt # Configure environment cp .env.example .env ``` ### 2. Run Quality Checks ```bash # Use the analyzer script python scripts/project_architect.py . # Review recommendations # Apply fixes ``` ### 3. Implement Best Practices Follow the patterns and practices documented in: - `references/architecture_patterns.md` - `references/system_design_workflows.md` - `references/tech_decision_guide.md` ## Best Practices Summary ### Code Quality - Follow established patterns - Write comprehensive tests - Document decisions - Review regularly ### Performance - Measure before optimizing - Use appropriate caching - Optimize critical paths - Monitor in production ### Security - Validate all inputs - Use parameterized queries - Implement proper authentication - Keep dependencies updated ### Maintainability - Write clear code - Use consistent naming - Add helpful comments - Keep it simple ## Common Commands ```bash # Development npm run dev npm run build npm run test npm run lint # Analysis python scripts/project_architect.py . python scripts/dependency_analyzer.py --analyze # Deployment docker build -t app:latest . docker-compose up -d kubectl apply -f k8s/ ``` ## Troubleshooting ### Common Issues Check the comprehensive troubleshooting section in `references/tech_decision_guide.md`. ### Getting Help - Review reference documentation - Check script output messages - Consult tech stack documentation - Review error logs ## Resources - Pattern Reference: `references/architecture_patterns.md` - Workflow Guide: `references/system_design_workflows.md` - Technical Guide: `references/tech_decision_guide.md` - Tool Scripts: `scripts/` directory ## When to Use This skill is applicable to execute the workflow or actions described in the overview.
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