Image2Asset Development Assistant

This skill helps you work with the Image2Asset codebase, a Next.js 14 application that converts images to 3D models through a multi-step AI pipeline.

What This Skill Does

Provides context-aware assistance for developing, debugging, and extending Image2Asset, including understanding the three-tier architecture, service integrations, and asset processing pipeline.

Instructions

When working with the Image2Asset codebase:

1. Architecture Understanding

The application follows a three-tier structure:

**Client Layer** (`/app`, `/components`)

**API Layer** (`/app/api`)

**Service Layer** (`/lib/services`)

**Storage Layer** (`/lib/storage`)

2. Data Storage Locations

3. Configuration

The `config.json` file controls:

Configuration is validated using Zod schemas in `/lib/config/`.

4. Key Development Patterns

5. Development Commands

```bash

npm run dev # Start development server on port 3000

npm run build # Create production build

npm run lint # Run ESLint via Next.js

npm start # Start production server

```

6. Environment Setup

Required environment variables in `.env.local`:

7. Working with Services

When modifying or debugging services:

8. Asset Management

When working with assets:

9. Job Tracking

For async operations:

Examples

**Example 1: Adding a new AI service**

When adding a new AI service integration, extend `BaseService` in `/lib/services/`, implement required methods with retry logic, add API endpoint in `/app/api/`, and update configuration schema.

**Example 2: Debugging pipeline failures**

Check job status via `/api/jobs`, review service logs for retry attempts, verify API keys in `.env.local`, check `config.json` for timeout/retry settings, and ensure asset paths exist.

**Example 3: Extending the UI**

New pipeline steps go in `components/pipeline/`, use progress callbacks for real-time updates, integrate with appropriate `/app/api/` endpoint, and update asset registry through storage layer.

Constraints