hackathon-ii_the-evolution-of-todo
π‘ Summary
A multi-phase project demonstrating the evolution of a todo application from a console app to a cloud-native AI chatbot using spec-driven development.
π― Target Audience
π€ AI Roast: βThis is less a finished skill and more a speculative roadmap for a multi-phase project, where the most concrete deliverable is a basic Python todo list.β
The README mentions database connections (DATABASE_URL) and shared secrets (BETTER_AUTH_SECRET) in environment files, posing a risk of credential exposure if these files are committed. It also plans for shell/container execution in later phases. Mitigation: Enforce .gitignore for all .env* files and use a secrets management service for production.
Hackathon II - The Evolution of Todo
Mastering Spec-Driven Development & Cloud-Native AI
This project demonstrates the evolution of a software application from a simple console app to a fully-featured, cloud-native AI chatbot deployed on Kubernetes. Built using Spec-Driven Development with Claude Code and Spec-Kit Plus.
Project Overview
This is a monorepo containing multiple phases of the Todo application evolution:
- β Phase I: Console App (Complete)
- π§ Phase II: Full-Stack Web Application (In Progress)
- β³ Phase III: AI Chatbot with MCP Server
- β³ Phase IV: Local Kubernetes Deployment
- β³ Phase V: Advanced Cloud Deployment
Quick Start
Phase 1 - Console App (Completed)
cd phase-1 uv venv source .venv/bin/activate # Windows: .venv/Scripts/activate uv sync python3 src/main.py
Phase 2 - Full-Stack Web App (In Progress)
Frontend (Next.js)
cd frontend npm install npm run dev # Opens on http://localhost:3000
Backend (FastAPI)
cd backend uv venv source .venv/bin/activate uv sync uvicorn main:app --reload # Opens on http://localhost:8000
Project Structure
Hackathon II/
βββ phase-1/ # β
Phase I: Python Console App (Complete)
β βββ src/ # Source code
β βββ tests/ # Unit tests
β βββ README.md # Phase 1 documentation
β
βββ frontend/ # π§ Phase II: Next.js Frontend (In Progress)
β βββ app/ # Next.js App Router pages
β βββ components/ # React components
β βββ lib/ # API client and utilities
β βββ CLAUDE.md # Frontend development guidelines
β
βββ backend/ # π§ Phase II: FastAPI Backend (In Progress)
β βββ routes/ # API endpoints
β βββ models.py # Database models
β βββ middleware/ # Authentication middleware
β βββ CLAUDE.md # Backend development guidelines
β
βββ specs/ # Centralized Specifications
β βββ overview.md # Project overview
β βββ architecture.md # System architecture
β βββ features/ # Feature specifications
β βββ api/ # API specifications
β βββ database/ # Database schemas
β βββ ui/ # UI specifications
β
βββ history/ # Prompt History Records & ADRs
β βββ prompts/ # Development history
β βββ adr/ # Architectural Decision Records
β
βββ .specify/ # Spec-Kit Plus templates and scripts
β βββ memory/
β β βββ constitution.md # Project principles
β βββ templates/ # Spec templates
β
βββ CLAUDE.md # Root development guidelines
βββ README.md # This file
Technology Stack
Phase I: Console App β
- Language: Python 3.13+
- Package Manager: UV
- UI: Rich (colorful CLI) + Inquirer (interactive menus)
- Storage: JSON file persistence
Phase II: Full-Stack Web App π§
- Frontend: Next.js 16+ (App Router), TypeScript, Tailwind CSS
- Backend: FastAPI, Python 3.13+
- Database: Neon Serverless PostgreSQL
- ORM: SQLModel
- Authentication: Better Auth with JWT tokens
- Deployment: Vercel (frontend) + Hugging Face (backend)
Phase III: AI Chatbot β³
- UI: OpenAI ChatKit
- AI Framework: OpenAI Agents SDK
- MCP Server: Official MCP SDK
- Database: Neon PostgreSQL (with conversations & messages)
Phase IV: Local Kubernetes β³
- Containerization: Docker with Docker AI (Gordon)
- Orchestration: Kubernetes (Minikube)
- Package Manager: Helm Charts
- AIOps: kubectl-ai, kagent
Phase V: Cloud Deployment β³
- Cloud Provider: DigitalOcean Kubernetes (DOKS)
- Messaging: Kafka on Redpanda Cloud
- Runtime: Dapr
- CI/CD: GitHub Actions
Features by Phase
Phase I (Complete) β
- Add, delete, update, view, mark complete tasks
- Interactive menu with colorful UI
- Command-line interface for scripts
- JSON persistence
- Input validation
Phase II (In Progress) π§
- Multi-user authentication (Better Auth + JWT)
- RESTful API with FastAPI
- Responsive web UI with Next.js
- Persistent storage in PostgreSQL
- User isolation and security
Phase III (Planned) β³
- Conversational task management
- Natural language understanding
- MCP tools for task operations
- Stateless chatbot with database persistence
Phase IV (Planned) β³
- Docker containerization
- Local Kubernetes deployment with Minikube
- Helm charts for package management
- AI-assisted DevOps (kubectl-ai, kagent)
Phase V (Planned) β³
- Recurring tasks with automated scheduling
- Due dates and reminders
- Event-driven architecture with Kafka
- Production deployment on DigitalOcean
- Full Dapr integration (Pub/Sub, State, Bindings, Secrets)
Development Approach
Spec-Driven Development (Required)
This project follows Spec-Driven Development:
- Write specifications in
/specs - Use Claude Code to generate implementation
- Refine specs until code is correct
- Manual coding is not allowed per constitution
Workflow
1. Write Spec β @specs/features/task-crud.md
2. Ask Claude Code β "Implement @specs/features/task-crud.md"
3. Claude Code generates code
4. Test and iterate on spec
5. Create Prompt History Record (PHR)
Documentation
- Hackathon Guide: Complete hackathon requirements
- Constitution: Project principles
- Overview: Project overview and status
- Architecture: System architecture across phases
- Root CLAUDE.md: Monorepo development guidelines
- Frontend CLAUDE.md: Frontend-specific guidelines
- Backend CLAUDE.md: Backend-specific guidelines
- Phase 1 README: Phase 1 documentation
Setup Instructions
Prerequisites
- Python 3.13+ (for backend and Phase 1)
- UV package manager for Python
- Node.js 18+ and npm/pnpm/yarn (for frontend)
- Git for version control
- PostgreSQL (Neon Serverless for Phase 2+)
Environment Variables
Frontend (.env.local)
NEXT_PUBLIC_API_URL=http://localhost:8000 BETTER_AUTH_SECRET=your-shared-secret-here BETTER_AUTH_URL=http://localhost:3000
Backend (.env)
DATABASE_URL=postgresql://user:password@host/database BETTER_AUTH_SECRET=your-shared-secret-here JWT_ALGORITHM=HS256
Important: BETTER_AUTH_SECRET must be identical in both frontend and backend.
Testing
Phase 1
cd phase-1 pytest tests/
Frontend
cd frontend npm test
Backend
cd backend pytest tests/
Deployment
Phase 2 Deployment
Frontend to Vercel
- Push code to GitHub
- Connect repository to Vercel
- Set environment variables in Vercel dashboard
- Deploy automatically on push
Backend to Hugging Face Spaces
- Create new Space (FastAPI template)
- Upload backend files
- Add secrets in Space settings
- Deploy
Scoring
| Phase | Points | Due Date | Status | |-------|--------|----------|--------| | Phase I | 100 | Dec 7, 2025 | β Complete | | Phase II | 150 | Dec 14, 2025 | π§ In Progress | | Phase III | 200 | Dec 21, 2025 | β³ Planned | | Phase IV | 250 | Jan 4, 2026 | β³ Planned | | Phase V | 300 | Jan 18, 2026 | β³ Planned | | Total | 1,000 | | |
Bonus Points
- Reusable Intelligence (Subagents/Skills): +200
- Cloud-Native Blueprints: +200
- Multi-language Support (Urdu): +100
- Voice Commands: +200
- Total Bonus: +600
Contributing
This is an individual hackathon project. Each participant submits separately.
Resources
- Claude Code Documentation
- Spec-Driven Development
- Nine Pillars of AI-Driven Development
- Neon Database
- FastAPI Documentation
- Next.js Documentation
License
This project is part of the Panaversity, PIAIC, and GIAIC Hackathon II.
Built with Claude Code + Spec-Kit Plus Hackathon II - The Evolution of Todo Version: 2.0.0 | Last Updated: 2025-12-08
Pros
- Well-structured monorepo with clear phase separation.
- Comprehensive documentation and spec-driven approach.
- Ambitious roadmap covering modern full-stack and cloud-native concepts.
Cons
- Not a single, deployable 'skill' but a collection of in-progress projects.
- Utility as an AI agent skill is low in its current state.
- High complexity and many dependencies for a simple core function.
Related Skills
pytorch
SβIt's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.β
agno
SβIt promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.β
nuxt-skills
SβIt's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.β
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author NaimalArain13.
