Install
$ agentstack add skill-tomas-u-claude-skills-technical ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Technical Architecture Skill
Provides comprehensive guidance on technical architecture and implementation decisions for full-stack applications, from system design to technology selection.
Quick Decision Guide
What do you need?
System architecture / Tech stack selection
→ Use: THIS skill (overall architecture, technology choices)
Security architecture / Threat modeling
→ Use: security skill (security patterns, compliance, risk)
Code review / Code quality
→ Use: code-review skill (line-by-line review, vulnerabilities)
CI/CD pipeline / Infrastructure / Deployment
→ Use: devops skill (pipelines, containers, monitoring)
UI/UX design / Wireframes / Mockups
→ Use: ux skill (user interface design, user flows)
Product planning / Feature prioritization
→ Use: product-owner skill (roadmap, user stories, backlog)
Scope of This Skill
This Skill Covers (Technical Architecture)
- ✅ Overall system architecture and service design
- ✅ Component architecture and code organization
- ✅ API design (REST, GraphQL, tRPC)
- ✅ Database schema and data modeling
- ✅ State management patterns
- ✅ Technology stack selection
- ✅ Performance optimization strategy
- ✅ Caching architecture
- ✅ Scalability planning
- ✅ Third-party service integration
- ✅ Frontend and backend patterns
Use Other Skills For
- ❌ Security architecture → Use security skill
- ❌ Code security review → Use code-review skill
- ❌ CI/CD pipelines → Use devops skill
- ❌ Infrastructure setup → Use devops skill
- ❌ UI/UX design → Use ux skill
- ❌ Product planning → Use product-owner skill
This Skill Works With Other Skills
- security skill → Technical arch provides structure, security validates it
- code-review skill → Technical arch defines patterns, code-review ensures compliance
- devops skill → Technical arch chooses stack, devops deploys it
- ux skill → UX defines user needs, technical arch implements them
Pre-Planning Checklist
Before starting architectural planning, gather:
Requirements
- [ ] What problem are we solving?
- [ ] Who are the users? (Students, teachers, admins, public)
- [ ] What are the core features?
- [ ] What's the expected scale? (users, data volume, traffic)
- [ ] What's the timeline? (MVP in weeks vs production in months)
Constraints
- [ ] Budget limitations?
- [ ] Team skills and size?
- [ ] Performance requirements? (response time, throughput)
- [ ] Compliance requirements? (GDPR, HIPAA, etc.)
- [ ] Integration requirements? (existing systems, APIs)
Context
- [ ] Starting from scratch or evolving existing system?
- [ ] Mobile, web, or both?
- [ ] Real-time features needed?
- [ ] Offline support needed?
- [ ] Global users or regional?
References to Load
- [ ] Frontend decisions → references/frontend-patterns.md
- [ ] Backend decisions → references/backend-patterns.md
- [ ] Database design → references/database-design.md
- [ ] Deployment/hosting → references/deployment-systems.md
Architecture Decision Framework
1. Understand Requirements
Start with the pre-planning checklist above.
2. Choose Architecture Pattern
Based on your stage and needs, select the appropriate pattern:
For MVPs / New Products:
- Pattern 1: Serverless Full-Stack (fast iteration, low maintenance)
For Growing Products:
- Pattern 3: Hybrid (pragmatic middle ground)
For Established Products:
- Pattern 2: Containerized Microservices (full control, scale)
See "Common Architecture Patterns" section below for details.
3. Select Technologies
Consult reference files for detailed guidance:
- Frontend: references/frontend-patterns.md
- Backend: references/backend-patterns.md
- Database: references/database-design.md
- Deployment: references/deployment-systems.md
4. Validate with Other Skills
Security validation:
- Use security skill to threat model your architecture
- Review authentication/authorization patterns
- Validate data protection approach
Code organization validation:
- Use code-review skill to establish coding standards
- Define maintainability criteria
Deployment validation:
- Use devops skill to design CI/CD pipeline
- Plan infrastructure and monitoring
5. Evaluate Tradeoffs
Every architecture decision involves tradeoffs:
Complexity vs Flexibility:
- Simple solutions are easier to maintain
- Complex solutions offer more flexibility
- Rule: Choose simplest solution that meets requirements
Performance vs Development Speed:
- Optimizations take time to implement
- Premature optimization wastes effort
- Rule: Optimize based on actual bottlenecks, not assumptions
Cost vs Scale:
- Serverless: Low cost at low scale, expensive at high scale
- Dedicated servers: Higher baseline cost, cheaper at scale
- Rule: Choose based on expected traffic patterns
Vendor Lock-in vs Convenience:
- Managed services (Vercel, Supabase) are convenient but lock you in
- Self-hosted solutions give flexibility but require maintenance
- Rule: Consider long-term strategic value and exit cost
Build vs Buy:
- Building gives control but takes time
- Buying gets you features fast but adds dependencies
- Rule: Buy for non-core features, build for competitive advantages
Common Architecture Patterns
Pattern 1: Serverless Full-Stack (Recommended for MVPs)
Stack:
Frontend: Next.js on Vercel
Backend: Next.js API Routes (serverless functions)
Database: Supabase (PostgreSQL) or PlanetScale (MySQL)
Cache: Upstash Redis
File Storage: Vercel Blob or S3
Auth: NextAuth.js or Clerk
When to use:
- ✅ New products/MVPs
- ✅ Small to medium scale ( $500/month at scale)
- Some vendor lock-in (but manageable)
- Cold start latency (200-500ms first request)
- Limited control over infrastructure
Migration path: When you outgrow this, move to Pattern 3 (Hybrid)
Pattern 2: Containerized Microservices (For Scale)
Stack:
Frontend: Next.js in containers (ECS/Kubernetes)
Backend: Node.js services in containers
Database: RDS PostgreSQL with read replicas
Cache: ElastiCache Redis
File Storage: S3
Auth: Custom JWT implementation
Message Queue: SQS or RabbitMQ
When to use:
- ✅ Proven product with growth (> 100k users)
- ✅ Need more control over infrastructure
- ✅ Complex business logic requiring service isolation
- ✅ Team has DevOps skills
- ✅ Predictable high traffic
Pros:
- Full control over infrastructure
- Better cost at scale ($500-2k/month for high traffic)
- Service isolation (can scale services independently)
- Technology flexibility (mix languages)
- No cold starts
Cons:
- More complex setup (weeks of infrastructure work)
- Requires DevOps expertise
- Higher baseline costs (minimum ~$200/month)
- More maintenance burden
Migration path: Usually don't migrate away, just add more services
Pattern 3: Hybrid (Pragmatic Middle Ground)
Stack:
Frontend: Next.js on Vercel (fast deploys, edge)
Backend: Dedicated API server on Railway/Render/Fly.io
Database: Managed PostgreSQL (Supabase/Neon/RDS)
Cache: Upstash Redis or managed Redis
File Storage: S3 or Cloudflare R2
Auth: NextAuth.js or custom
When to use:
- ✅ Outgrowing serverless costs (> $300/month)
- ✅ Not ready for full container complexity
- ✅ Need more backend flexibility (long-running tasks)
- ✅ Want good DX with more control
- ✅ Growing team (2-5 developers)
Pros:
- Better cost than pure serverless at scale
- More backend control (background jobs, websockets)
- Frontend still has great DX (Vercel)
- Easier than full microservices
- Good balance of control and convenience
Cons:
- More complex than pure serverless
- Need to manage API server
- Not as automated as Pattern 1
- Not as flexible as Pattern 2
Migration path: Can move to Pattern 2 when you need service isolation
Technology Selection Guidelines
Frontend Framework
Next.js (Recommended):
- ✅ Full-stack capabilities (API routes, server actions)
- ✅ Excellent performance (SSR, ISR, SSG)
- ✅ Great DX with Vercel
- ✅ Large ecosystem and community
- ✅ Built-in optimizations (images, fonts, code splitting)
- Use for: Most web applications, SEO-critical sites
React SPA:
- ✅ Simple deployment (static files)
- ✅ Full client-side control
- ✅ Works well with any backend
- ❌ Worse SEO (unless prerendering)
- ❌ Slower initial load
- Use for: Admin dashboards, internal tools, web apps where SEO doesn't matter
React Native (Mobile):
- ✅ Code sharing with web (if using React)
- ✅ Native performance
- ✅ Single codebase for iOS + Android
- ❌ More complex than web
- ❌ App store deployment overhead
- Use for: Mobile apps (student/guardian apps for educational app)
Backend Language/Runtime
Node.js/TypeScript (Recommended):
- ✅ Share code and types with frontend
- ✅ Great ecosystem (npm packages)
- ✅ Fast development (familiar to frontend devs)
- ✅ Good for I/O-heavy tasks (APIs, databases)
- ✅ Async by default
- Use for: Most applications, especially full-stack TypeScript
Python:
- ✅ Excellent for ML/AI workloads
- ✅ Great data processing libraries (pandas, numpy)
- ✅ Good for scripts and background jobs
- ❌ Harder to share code with frontend
- ❌ Slower for I/O-heavy tasks
- Use for: ML pipelines, data processing, computer vision, background jobs
When to use both:
- Node.js for API server (user-facing)
- Python for background processing (ML, data analysis)
Database
PostgreSQL (Recommended for most apps):
- ✅ Excellent for relational data
- ✅ ACID transactions (data integrity)
- ✅ Rich query capabilities (joins, aggregations)
- ✅ JSON support for flexibility
- ✅ Great performance with proper indexing
- ✅ Mature ecosystem
- Use for: Educational apps, CRUDs, any structured data
MongoDB:
- ✅ Flexible schema (good for rapid prototyping)
- ✅ Fast writes
- ✅ Good for unstructured data
- ❌ Weaker consistency guarantees
- ❌ No joins (application-level only)
- Use for: Rapid prototyping, analytics, logs, event data
Decision matrix:
- Structured data with relationships? → PostgreSQL
- Need ACID transactions? → PostgreSQL
- Flexible/evolving schema? → MongoDB or PostgreSQL (with JSONB)
- Heavy analytics? → PostgreSQL (with indexing) or ClickHouse
For detailed schema design, consult references/database-design.md
State Management
React Query/SWR (Recommended for server state):
- ✅ Handles 90% of state needs
- ✅ Automatic caching and refetching
- ✅ Loading/error states handled
- ✅ Less boilerplate than Redux
- ✅ Optimistic updates
- Use for: API data, server state, any data from backend
Zustand (Recommended for client state):
- ✅ Simple API
- ✅ Small bundle size ( 5 people
Approach:
- Identify service boundaries (auth, payments, notifications)
- Extract one service at a time (start with least critical)
- Add message queue (SQS, RabbitMQ) for async communication
- Set up service mesh (if using Kubernetes)
- Add centralized logging and monitoring
Timeline: 1-3 months
From Monorepo to Multiple Repos
When: Team > 10 people, clear service ownership
Approach:
- Extract shared code to npm packages
- Split services into separate repos
- Set up consistent CI/CD across repos
- Use dependency management (Renovate, Dependabot)
Timeline: 2-4 weeks
Getting Started
New Project Workflow
- Define requirements (use pre-planning checklist)
- Choose architecture pattern (serverless/hybrid/microservices)
- Select technologies (consult reference files)
- Design data model (references/database-design.md)
- Plan API structure (references/backend-patterns.md)
- Design frontend (references/frontend-patterns.md)
- Validate with security skill (threat model, security controls)
- Set up with devops skill (CI/CD, infrastructure)
- Document decisions (ADRs - Architecture Decision Records)
Existing Project Review Workflow
- Understand current architecture (diagram, document)
- Identify pain points (slow, expensive, hard to maintain)
- Assess against checklist (above)
- Identify gaps (missing caching, poor indexes, etc.)
- Propose improvements (prioritized by impact)
- Create migration plan (phased approach)
- Validate with other skills (security, code-review, devops)
Requesting Architectural Guidance
For best results, provide:
Context:
- What you're building (brief description)
- Current state (greenfield vs existing system)
- Team size and skills
Specific Question:
- What decision are you trying to make?
- What options are you considering?
- What's the tradeoff you're evaluating?
Constraints:
- Budget ($ per month)
- Timeline (MVP in 2 weeks vs production in 3 months)
- Scale requirements (expected users, traffic)
- Compliance (GDPR, HIPAA, etc.)
Example: > "I'm building an educational app for 1000 students and 50 teachers. Need task management, calendar, and file uploads. Team is 2 developers with React/Node.js skills. Budget is $100/month. Need MVP in 4 weeks. Should I use serverless or dedicated backend?"
This skill will consult the relevant references and provide context-specific, actionable recommendations.
Reference Files
Load these for detailed guidance:
- references/frontend-patterns.md - React/Next.js patterns, state management, performance
- references/backend-patterns.md - API design, authentication, caching, background jobs
- references/database-design.md - Schema design, indexing, migrations, scaling
- references/deployment-systems.md - Hosting platforms, CI/CD, monitoring
For comprehensive coverage, use with:
- security skill - Security architecture, threat modeling, compliance
- code-review skill - Code quality, testing strategy, maintainability
- devops skill - CI/CD pipelines, infrastructure, deployment
- ux skill - User interface design, user flows, wireframes
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: tomas-u
- Source: tomas-u/claude-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.