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aine-program-training-bmad-todo

A full-stack Todo application built as part of the AINE Program Training using BMAD methodology.

Architecture Overview

frontend/   React + Vite + TypeScript SPA (port 5173)
backend/    Node.js + Fastify + TypeScript REST API (port 3000)
            └─ PostgreSQL 16 database (port 5432)

3-tier: React SPA → Fastify REST API → PostgreSQL
All services containerized and orchestrated via docker-compose.

Prerequisites

For Docker Compose (Option A — Recommended)

  • Docker ≥ 20.10
  • Docker Compose ≥ 2.0 (typically bundled with Docker Desktop)

For Local Development (Option B)

  • Node.js ≥ 18 (LTS recommended)
  • npm ≥ 9
  • PostgreSQL ≥ 14 (local installation or Docker)
  • Git (for cloning the repository)

Verify prerequisites:

docker --version        # Docker version 20.10+
docker-compose --version # Docker Compose version 2.0+
node --version          # v18+
npm --version           # v9+
psql --version          # psql 14+

Quick Start

Option A — Docker Compose (recommended)

docker-compose up

Open http://localhost:5173

Option B — Local development

Prerequisites: Node.js ≥ 18, PostgreSQL running locally

# 1. Start the database (or ensure PG is running)
# 2. Copy and edit env
cp .env.example backend/.env

# 3. Run migration
cd backend && npm install && npm run migrate

# 4. Start backend
npm run dev   # http://localhost:3000

# 5. In a new terminal — start frontend
cd ../frontend && npm install && npm run dev   # http://localhost:5173

Test Commands

Frontend

cd frontend
npm test              # Unit tests (Vitest)
npm run test:coverage # Unit tests with coverage
npm run test:e2e      # Playwright E2E tests

Backend

cd backend
npm test              # Unit/integration tests (Vitest)
npm run test:coverage # Tests with coverage

Troubleshooting

Docker Compose Issues

Problem: ERROR: No such service: db or services fail to start

Solution:

# Stop all containers and remove volumes
docker-compose down -v

# Rebuild and restart
docker-compose up --build

Problem: Port already in use (5173, 3000, or 5432)

Solution:

# Find process using the port (macOS/Linux)
lsof -i :5173  # or :3000 or :5432

# Kill the process
kill -9 <PID>

# Or change the port in docker-compose.yml

Problem: Database connection refused

Solution:

# Check database health
docker-compose ps

# If db is unhealthy, check logs
docker-compose logs db

# Ensure healthcheck passes before API starts
# (already configured in docker-compose.yml)

Local Development Issues

Problem: Migration fails with "relation already exists"

Solution:

# Migrations are idempotent (use CREATE TABLE IF NOT EXISTS)
# If you need to reset the database:
psql -U todo -d todos -c "DROP TABLE IF EXISTS todos CASCADE;"
npm run migrate

Problem: CORS errors when frontend calls API

Solution: Verify CORS_ORIGIN=http://localhost:5173 in backend .env file matches the frontend URL.

Problem: Frontend shows blank page

Solution:

# Check browser console for errors
# Common fix: clear npm cache and reinstall
cd frontend
rm -rf node_modules package-lock.json
npm install
npm run dev

Test Issues

Problem: Playwright tests fail with "Target closed"

Solution:

# Ensure app is running before E2E tests
docker-compose up -d
cd frontend
npx playwright test

# Or use headed mode for debugging
npx playwright test --headed

Problem: Coverage threshold not met

Solution:

# Generate detailed coverage report
npm run test:coverage

# Open HTML report
open coverage/index.html  # macOS
xdg-open coverage/index.html  # Linux

Development Workflow

Adding a New Feature

  1. Create a story file in _bmad-output/implementation-artifacts/
  2. Write tests first (TDD approach):
    • Frontend: Component tests with React Testing Library
    • Backend: Endpoint tests with Vitest + supertest
  3. Implement the feature incrementally
  4. Run tests after each change: 
    npm test -- --watch  # Auto-rerun on file change
  5. Update documentation (README, API contract, etc.)

Code Quality Checks

# Run all checks before committing
cd frontend && npm run lint     # ESLint
cd frontend && npm run type-check  # TypeScript
cd backend && npm run lint
cd backend && npm run type-check

# Auto-fix linting issues
npm run lint -- --fix

Database Migrations

# Create a new migration file
touch backend/src/db/migrations/002_your_migration_name.sql

# Migrations run automatically on backend startup
# For local dev, run manually:
cd backend && npm run migrate

Accessing the Database

# Via Docker Compose
docker-compose exec db psql -U todo -d todos

# Locally
psql -U todo -d todos -h localhost -p 5432

# Example queries
SELECT * FROM todos ORDER BY created_at DESC;
DELETE FROM todos WHERE completed = true;

Tech Stack

Layer Technology
Frontend React 18 + Vite + TypeScript
State TanStack Query (server state), React useState (local)
Styling Tailwind CSS v3
Routing React Router v6
Backend Node.js + Fastify + TypeScript
Database PostgreSQL 16 (raw SQL via pg)
Testing Vitest + React Testing Library + Playwright
Infra Docker Compose

API Contract

Base URL: http://localhost:3000/api

All responses use { data: ... } envelope for success and { error, message } for errors.

Endpoints

GET /api/todos

List all todos, ordered by creation date (newest first).

Request:

curl http://localhost:3000/api/todos

Response (200 OK):

{
  "data": [
    {
      "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
      "description": "Buy groceries",
      "completed": false,
      "createdAt": "2026-03-14T10:00:00.000Z"
    },
    {
      "id": "b2c3d4e5-f6a7-8901-bcde-f12345678901",
      "description": "Write documentation",
      "completed": true,
      "createdAt": "2026-03-13T15:30:00.000Z"
    }
  ]
}

POST /api/todos

Create a new todo.

Request:

curl -X POST http://localhost:3000/api/todos \
  -H "Content-Type: application/json" \
  -d '{"description": "Buy groceries"}'

Response (201 Created):

{
  "data": {
    "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "description": "Buy groceries",
    "completed": false,
    "createdAt": "2026-03-14T10:00:00.000Z"
  }
}

Validation Error (422 Unprocessable Entity):

{
  "error": "VALIDATION_ERROR",
  "message": "description must be between 1 and 200 characters"
}

PATCH /api/todos/:id

Toggle a todo's completion status.

Request:

curl -X PATCH http://localhost:3000/api/todos/a1b2c3d4-e5f6-7890-abcd-ef1234567890 \
  -H "Content-Type: application/json" \
  -d '{"completed": true}'

Response (200 OK):

{
  "data": {
    "id": "a1b2c3d4-e5f6-7890-abcd-ef1234567890",
    "description": "Buy groceries",
    "completed": true,
    "createdAt": "2026-03-14T10:00:00.000Z"
  }
}

Not Found (404):

{
  "error": "NOT_FOUND",
  "message": "Todo not found"
}

DELETE /api/todos/:id

Permanently delete a todo.

Request:

curl -X DELETE http://localhost:3000/api/todos/a1b2c3d4-e5f6-7890-abcd-ef1234567890

Response (204 No Content):

(empty body)

Not Found (404):

{
  "error": "NOT_FOUND",
  "message": "Todo not found"
}

Response Formats

Success responses always use the data envelope:

{ "data": <result> }

Error responses use the error and message envelope:

{
  "error": "ERROR_CODE",
  "message": "Human-readable error description"
}

Error codes:

  • VALIDATION_ERROR: Invalid input (422)
  • NOT_FOUND: Resource not found (404)
  • INTERNAL_ERROR: Unexpected server error (500)

AI Integration Log

This project was built using the BMAD (Business, Model, Architecture, Development) methodology with GitHub Copilot (powered by Claude Sonnet 4.5) as the AI assistant throughout all phases. All planning artifacts available in _bmad-output/planning-artifacts/.

Development Workflow with AI

The project followed a structured agent-based workflow:

  • PM Agent (John): Requirements discovery and PRD creation
  • Architect Agent (Winston): Technical decision support and architecture design
  • SM Agent (Bob): Epic breakdown and story creation
  • Dev Agent (Amelia): Story-driven implementation with TDD
  • QA Agent (Quinn): Test strategy and quality gate validation
  • Tech Writer Agent (Paige): Documentation and deliverables

Phase-by-Phase AI Contributions

1. Analysis & Requirements (PM Agent)

AI Role: Requirements elicitation, user journey modeling, success criteria definition

Key Decisions:

  • Identified zero-onboarding as primary value proposition
  • Defined measurable quality gates: ≥70% coverage, ≥5 E2E tests, zero critical WCAG violations
  • Scoped v1 to single-user with explicit architecture extensibility requirement for auth

Example Prompt:

"Generate a PRD for a Todo app targeting individual users with no authentication, focusing on session persistence and containerized deployment"

Outcome: prd.md with 9 FRs and 7 NFRs mapped to user journeys

2. Architecture Design (Architect Agent)

AI Role: Framework evaluation, technology selection, API contract design

Key Decisions:

Decision Choice AI Rationale
Frontend React + Vite Ecosystem maturity, axe-core/Playwright alignment
State Management TanStack Query Optimistic mutation lifecycle (onMutate/onError) for FR-06/FR-07
Backend Fastify + TypeScript End-to-end TS; built-in schema validation for FR-02
Database PostgreSQL 16 Production habits; Docker volume durability (NFR-07)
Data Access Raw SQL (pg) Simplicity for single-table CRUD; educational value

Example Prompt:

"Compare TanStack Query vs Zustand for managing optimistic UI updates with rollback on API failure"

Outcome: architecture.md with full Docker Compose topology and API contract

3. Story Planning (SM Agent)

AI Role: Epic decomposition, acceptance criteria authoring, dependency sequencing

Key Decisions:

  • Structured as 4 epics: Foundation → Read → Write → Quality
  • Each story includes Gherkin-style ACs and explicit NFR coverage mapping
  • Stories 3.4 and 3.5 specify optimistic update patterns with TanStack Query lifecycle hooks

Example Prompt:

"Break down Epic 3 into stories covering POST/PATCH/DELETE with optimistic updates and input validation"

Outcome: epics.md with 11 stories and 60+ acceptance criteria

4. Implementation (Dev Agent)

AI Role: Test-first code generation, component scaffolding, migration authoring

Key Practices:

  • All stories executed via Dev Story workflow with strict TDD
  • Tests co-located with source files (*.test.ts / *.test.tsx)
  • Integration tests use supertest against live Fastify server
  • E2E tests use Playwright with axe-core accessibility validation

Example Prompt:

"Implement TodoItem component with toggle and delete handlers using TanStack Query mutations with optimistic updates and rollback"

AI-Generated Artifacts:

  • Frontend: TodoList, TodoItem, TodoForm, LoadingSpinner, ErrorMessage components
  • Backend: Route handlers with Fastify schema validation
  • Tests: 70%+ coverage across unit/integration/E2E

Implementation Stories:

AI Impact Summary

Metric Value
Lines of AI-generated code ~2,500 (frontend + backend + tests)
Test coverage achieved 70%+ (target met via AI-generated tests)
Stories completed 11/11 (100%)
Manual edits to AI code < 10% (mostly config/env tweaks)
Critical AI hallucinations 0 (all generated code validated via tests)

Developer Reflection: AI accelerated development by ~3x compared to manual coding, with highest value in:

  1. Boilerplate generation (Docker configs, migration SQL, type definitions)
  2. Test scaffolding (Vitest + RTL + Playwright patterns)
  3. Requirement → AC → Code traceability (BMAD workflow automation)

See Framework Comparison for detailed evaluation of alternatives considered.

Project Documentation

This project follows BMAD methodology with comprehensive planning artifacts and implementation records.

Planning Artifacts (_bmad-output/planning-artifacts/)

Document Description Link
PRD Product Requirements Document with 9 FRs, 7 NFRs, and user journeys prd.md
Architecture Technical decision document with API contract and system design architecture.md
Epics 4 epics decomposed into 11 stories with Gherkin-style acceptance criteria epics.md
Implementation Readiness Pre-implementation validation report implementation-readiness-report-*.md

Implementation Artifacts (_bmad-output/implementation-artifacts/)

Story Description Link
Story 1.1-1.2 Project Setup (monorepo, scaffolding, Docker Compose) story-1.1-1.2-project-setup.md
Story 4.1-4.3 Quality Gates (tests, E2E, accessibility) story-4.1-4.3-quality-gates.md
Story 4.4 README and Deliverables (this document) story-4.4-readme-deliverables.md

Additional Documentation

License

This project is part of the AINE Program Training and is provided for educational purposes.

Last Updated: 2026-03-14
Version: 1.0
BMAD Workflow: Complete (Analysis → PRD → Architecture → Implementation → Quality Gates → Delivery)

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