Can I vibe code Omnia Retail?

Build a dynamic pricing backend engine using Node.js, TypeScript, PostgreSQL, and Prisma ORM.

1. DATA MODEL:
- Store Product: id, sku, title, cost_price, current_price, min_margin_percent, target_margin_percent, shopify_variant_id.
- Competitor Target: id, store_product_id, competitor_name, target_url, selector_css, last_scraped_price, updated_at.
- Pricing Rule: id, store_product_id, strategy (COST_PLUS, MATCH_COMPETITOR, BEAT_COMPETITOR), adjustment_flat, adjustment_percent, floor_price, ceiling_price.
- Price Log: id, store_product_id, old_price, new_price, trigger_reason, created_at.

2. CORE FUNCTIONALITY:
- Scraper Module: A scheduled job using Crawlee with headless Chromium to fetch target_url, extract price using selector_css, and handle basic anti-bot delays.
- Rule Calculation Engine: A function that takes current scraped competitor price, checks floor_price and min_margin_percent against cost_price, calculates the optimal price, and records a Price Log.
- Integration Queue: A BullMQ queue that receives calculated price changes and executes batched updates against the Shopify GraphQL Admin API (productVariantUpdate).

3. SAFETY AND EDGE CASES:
- Never calculate a price below (cost_price * (1 + min_margin_percent / 100)).
- If a scraped price drops by more than 30% in a single check, flag it for human review instead of auto-repricing.
- Exponential backoff on rate-limited Shopify API calls.

4. OUT OF SCOPE:
- Do not build complex ML elasticity algorithms. Use explicit user-configured business rules only.

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