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/tech-stack-recommender

Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.

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$ npx -y skills add alirezarezvani/claude-cto-team --skill tech-stack-recommender --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/tech-stack-recommender

Context preview

The summary Claude sees to decide when to auto-load this skill.

Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.

SKILL.md

tech-stack-recommender.SKILL.md
name: tech-stack-recommender
description: Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.

Tech Stack Recommender

Provides structured recommendations for technology stack selection based on project requirements, team constraints, and business goals.

When to Use

  • Starting a new project and need stack recommendations
  • Evaluating technology options for specific use cases
  • Comparing frameworks or languages for a project
  • Assessing team readiness for a technology choice
  • Planning technology migrations

Stack Selection Framework

Decision Inputs

┌───────────────────────────────────────────────────────────────────┐
│                    STACK SELECTION INPUTS                         │
├───────────────────────────────────────────────────────────────────┤
│                                                                   │
│  Project Requirements     Team Factors        Business Constraints│
│  ────────────────────     ────────────        ──────────────────  │
│  • Scale expectations     • Current skills    • Time to market    │
│  • Performance needs      • Learning capacity • Budget            │
│  • Integration points     • Team size         • Hiring market     │
│  • Compliance/Security    • Experience level  • Long-term support │
│                                                                   │
└───────────────────────────────────────────────────────────────────┘
                              │
                              ▼
                    ┌─────────────────┐
                    │ RECOMMENDATION  │
                    │   Framework     │
                    └─────────────────┘

---

Quick Stack Recommendations

By Project Type

| Project Type | Frontend | Backend | Database | Why | |--------------|----------|---------|----------|-----| | **SaaS MVP** | Next.js | Node.js/Express | PostgreSQL | Fast iteration, full-stack JS | | **E-commerce** | Next.js | Node.js or Python | PostgreSQL + Redis | SEO, caching, transactions | | **Mobile App** | React Native | Node.js/Python | PostgreSQL | Cross-platform, shared logic | | **Real-time App** | React | Node.js + WebSocket | PostgreSQL + Redis | Event-driven, low latency | | **Data Platform** | React | Python/FastAPI | PostgreSQL + ClickHouse | Data processing, analytics | | **Enterprise** | React | Java/Spring or .NET | PostgreSQL/Oracle | Stability, enterprise support | | **ML Product** | React | Python/FastAPI | PostgreSQL + Vector DB | ML ecosystem, inference |

By Team Profile

| Team Profile | Recommended Stack | Avoid | |--------------|-------------------|-------| | **Full-stack JS** | Next.js, Node.js, PostgreSQL | Go, Rust (learning curve) | | **Python Background** | FastAPI, React, PostgreSQL | Heavy frontend frameworks | | **Enterprise Java** | Spring Boot, React, PostgreSQL | Bleeding-edge tech | | **Startup (Speed)** | Next.js, Supabase/Firebase | Complex microservices | | **Scale-Up** | React, Go/Node, PostgreSQL | Monolithic frameworks |

---

Technology Comparison Tables

Frontend Frameworks

| Framework | Best For | Learning Curve | Ecosystem | Hiring | |-----------|----------|----------------|-----------|--------| | **React** | Complex UIs, SPAs | Medium | Excellent | Easy | | **Next.js** | Full-stack, SSR, SEO | Medium | Excellent | Easy | | **Vue.js** | Simpler apps, gradual adoption | Easy | Good | Medium | | **Svelte** | Performance-critical | Easy | Growing | Hard | | **Angular** | Enterprise, large teams | Hard | Good | Medium |

React vs Vue vs Angular

                Speed to MVP    Long-term Maint    Enterprise Ready
React           ████████░░      ████████░░         █████████░
Vue             █████████░      ███████░░          ██████░░░░
Angular         ██████░░░░      █████████░         ██████████

Backend Frameworks

| Framework | Language | Best For | Performance | Ecosystem | |-----------|----------|----------|-------------|-----------| | **Express** | Node.js | APIs, real-time | Good | Excellent | | **Fastify** | Node.js | High-performance APIs | Excellent | Good | | **FastAPI** | Python | ML APIs, async | Excellent | Good | | **Django** | Python | Full-featured apps | Good | Excellent | | **Spring Boot** | Java | Enterprise | Good | Excellent | | **Go (Gin/Echo)** | Go | High performance | Excellent | Good | | **Rails** | Ruby | Rapid prototyping | Moderate | Good | | **NestJS** | TypeScript | Structured Node apps | Good | Good |

When to Use What

## Node.js (Express/Fastify/NestJS)
✅ Real-time applications (WebSocket)
✅ I/O-heavy workloads
✅ Full-stack JavaScript teams
✅ Microservices
❌ CPU-intensive tasks
❌ Heavy computation

## Python (FastAPI/Django)
✅ ML/Data Science integration
✅ Rapid prototyping
✅ Data processing pipelines
✅ Scientific computing
❌ High-concurrency I/O
❌ Real-time systems

## Go
✅ High-performance services
✅ System programming
✅ Concurrent workloads
✅ Microservices at scale
❌ Rapid prototyping
❌ Complex ORM needs

## Java (Spring Boot)
✅ Enterprise applications
✅ Complex business logic
✅ Transaction-heavy systems
✅ Large teams
❌ Quick MVPs
❌ Small projects

Databases

| Database | Type | Best For | Scale | Complexity | |----------|------|----------|-------|------------| | **PostgreSQL** | Relational | General purpose, ACID | High | Medium | | **MySQL** | Relational | Web apps, read-heavy | High | Low | | **MongoDB** | Document | Flexible schemas, JSON | High | Low | | **Redis** | Key-Value | Caching, sessions | Very High | Low | | **Elasticsearch** | Search | Full-text search | High | Medium | | **ClickHouse** | Columnar | Analytics, time-series | Very High | Medium | | **DynamoDB** | Key-Value | Serverless, AWS | Very High | Medium | | **Cassandra** | Wide-column | Write-heavy, distributed | Very High | High |

Database Selection Guide

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