dc95fc109e
- Standardized pool imports to use default export consistently
- Changed from named import { pool } to default import pool
- Resolves "Cannot find module" errors in CI environment
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
MotoVaultPro - AI Onboarding Guide
For AI Assistants: Instant Codebase Understanding
To efficiently understand and maintain this codebase, follow this exact sequence:
1. Load Core Context (Required - 2 minutes)
Read these files in order:
1. AI_PROJECT_GUIDE.md - Complete project overview and architecture
2. .ai/context.json - Loading strategies and feature metadata
3. docs/README.md - Documentation navigation hub
2. Understand the Architecture (30 seconds)
Modified Feature Capsules: Each feature in backend/src/features/[name]/ is 100% self-contained with everything needed in one directory. No shared business logic.
3. For Specific Tasks
Working on a Feature
Load entire feature directory: backend/src/features/[feature-name]/
- Start with README.md for complete API and business rules
- Everything needed is in this single directory
Cross-Feature Work
Load each feature's index.ts and README.md
Database Work
Load docs/database-schema.md for complete schema overview
Testing Work
Load docs/testing.md for Docker-based testing workflow
4. Development Environment (1 command)
make dev # Starts complete Docker environment
5. Key Principles
- Docker-First: All development in containers, no local installs
- Feature Independence: Each feature is completely isolated
- Single Directory Context: Load one directory for complete understanding
- User-Scoped Data: All data isolated by user_id
6. Common Tasks
# Test specific feature
npm test -- features/vehicles
# Run migrations
make migrate
# View logs
make logs
# Container shell access
make shell-backend
7. Feature Status
- vehicles: Complete (primary entity, VIN decoding)
- fuel-logs: Implemented (depends on vehicles)
- maintenance: Scaffolded (depends on vehicles)
- stations: Partial (Google Maps integration)
Architecture Summary
Vehicle management platform using Modified Feature Capsule design where each feature is self-contained with API, domain logic, database layer, migrations, external integrations, tests, and documentation in a single directory. Built for AI maintainability with Docker-first development.
Quick Navigation
- Setup: AI_PROJECT_GUIDE.md
- Features: backend/src/features/[name]/README.md
- Database: docs/database-schema.md
- Testing: docs/testing.md
- Security: docs/security.md