# Template Overview – AI Coding Starter Kit **Erstellt:** 2026-01-10 **Version:** 1.3.0 **Für:** Production-Ready AI-Powered Development Template --- ## Was ist in diesem Template? ### ✅ Vollständig konfiguriertes Next.js 16 Projekt - TypeScript (strict mode) - Tailwind CSS (configured) - ESLint 9 (Next.js defaults) - App Router (not Pages Router) - Responsive Starter Page - Supabase-Ready (optional) ### ✅ 6 Production-Ready AI Agents (in `.claude/agents/`) 1. **requirements-engineer.md** – Feature Specs mit interaktiven Fragen 2. **solution-architect.md** – PM-friendly Tech-Design (keine Code-Snippets) 3. **frontend-dev.md** – React Components + Automatic Handoff zu Backend/QA 4. **backend-dev.md** – Supabase APIs + **Performance Best Practices** 5. **qa-engineer.md** – Manual Testing + Regression Tests 6. **devops.md** – Vercel Deployment + **Production-Ready Essentials** ### ✅ Production-Ready Features (NEW in v1.3) **DevOps Agent enthält:** - Error Tracking Setup (Sentry) - Security Headers (XSS/Clickjacking Protection) - Environment Variables Best Practices - Performance Monitoring (Lighthouse) **Backend Agent enthält:** - Database Indexing Guidelines - Query Performance Optimization (N+1 Problem) - Caching Strategy (Next.js) - Input Validation (Zod) - Rate Limiting (optional) ### ✅ Project Structure (best practices) ``` ai-coding-starter-kit/ ├── .claude/ │ └── agents/ ← 6 AI Agents (Production-Ready) ├── features/ ← Feature Specs (Requirements Engineer creates these) │ └── README.md ← How to write Feature Specs ├── test-reports/ ← QA Test Reports (QA Engineer creates these) │ └── README.md ← Test Report Format ├── src/ │ ├── app/ ← Pages (Next.js App Router) │ ├── components/ ← React Components │ │ └── ui/ ← shadcn/ui components (add as needed) │ └── lib/ ← Utilities │ ├── supabase.ts ← Supabase Client (commented out by default) │ └── utils.ts ← Helper Functions ├── public/ ← Static files (favicon, images) ├── PROJECT_CONTEXT.md ← Project Documentation (updated with Prod-Ready notes) ├── FEATURE_CHANGELOG.md ← Feature Tracking (Agents read this!) ├── TEMPLATE_CHANGELOG.md ← Template Version History (v1.0 - v1.3) ├── HOW_TO_USE_AGENTS.md ← Agent Usage Guide ├── .env.local.example ← Environment Variables Template └── package.json ← Dependencies (ESLint 9, Supabase, Tailwind) ``` ### ✅ Documentation - **README.md** – Quick-Start Guide - **PROJECT_CONTEXT.md** – Project Template (with Production-Ready section) - **FEATURE_CHANGELOG.md** – Feature Tracking System (Agents use this!) - **TEMPLATE_CHANGELOG.md** – Template Version History - **HOW_TO_USE_AGENTS.md** – How to use Agents (not Skills!) - **features/README.md** – Feature Spec Guidelines - **test-reports/README.md** – Test Report Format ### ✅ Agent Workflow Features - **Interactive Requirements:** `AskUserQuestion` Tool für strukturierte Inputs - **PM-Friendly Output:** Solution Architect schreibt für Product Manager, nicht für Devs - **Automatic Handoffs:** Frontend → Backend Check → QA Handoff (automatic) - **FEATURE_CHANGELOG.md Integration:** Alle Agents lesen bestehende Features (Code-Reuse!) - **Production Checklists:** In DevOps + Backend Agents integriert ### ✅ Ready-to-Deploy - Vercel-optimized - Environment Variables Template - .gitignore (Node, .env, etc.) - TypeScript + Tailwind + ESLint configured - Production-Ready Guides included --- ## Was der User noch tun muss ### 1. Template anpassen - **PROJECT_CONTEXT.md** ausfüllen (Project Name, Vision, Features) - **package.json** name anpassen (optional) ### 2. Supabase einrichten (optional) Falls Backend genutzt wird: - Supabase Project erstellen - `.env.local` mit Credentials füllen - `src/lib/supabase.ts` aktivieren (uncomment code) ### 3. shadcn/ui Components hinzufügen (nach Bedarf) ```bash npx shadcn@latest add button npx shadcn@latest add card # etc. ``` ### 4. Erste Feature bauen ```bash # Tell Claude in Chat: "Read .claude/agents/requirements-engineer.md and create a feature spec for [your idea]" ``` ### 5. Production Setup (beim ersten Deployment) Folge DevOps Agent Guides: - Error Tracking (Sentry) – 5 Minuten Setup - Security Headers (`next.config.js`) – Copy-Paste - Performance Check (Lighthouse) – Built-in Chrome DevTools --- ## Template Updates (Changelog) ### v1.3.0 (2026-01-12) – Production-Ready Essentials - ✅ DevOps Agent: Error Tracking, Security Headers, Performance Monitoring - ✅ Backend Agent: Database Indexing, Query Optimization, Caching, Input Validation - ✅ PROJECT_CONTEXT.md: Production-Ready Features Section ### v1.2.0 (2026-01-10) – FEATURE_CHANGELOG System - ✅ Alle Agents lesen FEATURE_CHANGELOG.md (Code-Reuse!) - ✅ DevOps Agent updated FEATURE_CHANGELOG.md nach Deployment ### v1.1.0 (2026-01-10) – Agent System Improvements - ✅ `.claude/skills/` → `.claude/agents/` umbenannt (kein Conflict mit Claude Skills) - ✅ Requirements Engineer nutzt `AskUserQuestion` Tool - ✅ Solution Architect: PM-friendly Output (keine Code-Snippets) - ✅ Frontend Developer: Automatic Backend Check + QA Handoff - ✅ HOW_TO_USE_AGENTS.md erstellt ### v1.0.0 (2026-01-10) – Initial Release - ✅ Next.js 16 + TypeScript + Tailwind CSS - ✅ 6 AI Agents (Requirements, Architect, Frontend, Backend, QA, DevOps) - ✅ Feature Specs System (`/features/PROJ-X.md`) - ✅ PROJECT_CONTEXT.md Template --- ## GitHub Repository Setup ### Schritt 1: Neues GitHub Repo erstellen 1. Gehe zu GitHub.com 2. Erstelle neues Repo: `ai-coding-starter-kit` 3. **Wichtig:** Erstelle KEIN README, keine .gitignore (alles schon im Template) ### Schritt 2: Push Template zu GitHub ```bash cd /Users/alexandersprogis/alex-bmad-projects/ai-coding-starter-kit git init git add . git commit -m "Initial commit: AI Coding Starter Kit v1.3.0 (Production-Ready)" git branch -M main git remote add origin https://github.com/YOUR_USERNAME/ai-coding-starter-kit.git git push -u origin main ``` ### Schritt 3: Im Guide/Lead Magnet verlinken Ersetze `YOUR_USERNAME` mit deinem echten GitHub Username --- ## Template Maintenance ### Wenn Next.js updatet ```bash npm install next@latest react@latest react-dom@latest npm install eslint-config-next@latest ``` ### Wenn Agent-Files upgedatet werden - Kopiere neue Versionen - Paste in `.claude/agents/` - Update TEMPLATE_CHANGELOG.md ### Wenn neue Agents hinzukommen - Füge neuen Agent-File zu `.claude/agents/` hinzu - Update README.md (Liste der verfügbaren Agents) - Update PROJECT_CONTEXT.md (Agent-Team Verantwortlichkeiten) --- ## User Testing Checklist Bevor du das Template als Lead Magnet veröffentlichst: ### Basic Functionality - [ ] `npm install` funktioniert ohne Errors - [ ] `npm run dev` startet Server auf localhost:3000 - [ ] `npm run build` läuft ohne Errors - [ ] Starter Page zeigt korrekt an ### Agent System - [ ] Alle 6 Agents sind in `.claude/agents/` vorhanden - [ ] Agents sind vollständig (keine TODOs oder Placeholders) - [ ] FEATURE_CHANGELOG.md ist vorhanden (mit Template) - [ ] TEMPLATE_CHANGELOG.md ist aktuell (v1.3.0) ### Documentation - [ ] `PROJECT_CONTEXT.md` ist vollständig (inkl. Production-Ready Section) - [ ] `README.md` hat klare Quick-Start Anleitung - [ ] `HOW_TO_USE_AGENTS.md` erklärt Agent-Nutzung - [ ] `features/README.md` erklärt Feature Spec Format - [ ] `test-reports/README.md` erklärt Test Report Format ### Configuration - [ ] `.env.local.example` ist vorhanden - [ ] `.gitignore` enthält `.env.local`, `node_modules`, etc. - [ ] `package.json` Dependencies sind aktuell ### Production-Ready Guides - [ ] DevOps Agent: Error Tracking Section vollständig - [ ] DevOps Agent: Security Headers Section vollständig - [ ] Backend Agent: Database Indexing Section vollständig - [ ] Backend Agent: Input Validation Section vollständig ### GitHub - [ ] GitHub Repo ist public (für Lead Magnet) - [ ] Clone + Install funktioniert in frischem Ordner - [ ] README hat korrekte Clone-URL --- ## Fertig! 🚀 **Template ist bereit für:** 1. Push zu GitHub 2. Lead Magnet / Public Template 3. User Testing 4. Production-Ready App Development **Nächster Schritt:** Push zu GitHub, teste Clone in frischem Ordner, dann veröffentlichen! --- ## Lead Magnet Positioning **Headline:** "AI Coding Starter Kit – Production-Ready Template with AI-Powered Development Workflow" **Key Features:** - ✅ 6 Specialized AI Agents (Requirements → Deployment) - ✅ Production-Ready Guides (Error Tracking, Security, Performance) - ✅ Automatic Code-Reuse System (FEATURE_CHANGELOG) - ✅ PM-Friendly Documentation (no code in specs) - ✅ Built for Scale (Database Indexing, Query Optimization) **Target Audience:** - Product Managers ohne Deep-Tech Background - Solo Founders building MVPs - Small Teams (2-5 people) ohne DevOps Engineer **Value Proposition:** "Build production-ready, scalable apps faster – with AI agents handling Requirements, Architecture, Development, QA, and Deployment."