Can AI replace Europe-Camions?

Build a local truck shopping tracker called RigWatch. Single user, runs on my laptop, no accounts, no cloud, no telemetry.

Stack, no substitutions: Node 20, TypeScript, Express, better-sqlite3, EJS templates, plain CSS. No React, no ORM, no Docker.

Data model in SQLite:
- vehicle: id, title, make, model, year, mileage_km, engine_power_hp, axle_config, euro_class, body_type, country, dealer_name, source_url, notes, status (watching | contacted | rejected | bought), created_at
- price_point: id, vehicle_id, amount_cents, currency, seen_on (date)
- alert_event: id, vehicle_id, kind (price_drop | price_rise | stale), message, created_at, seen (bool)

Features, all server rendered:
1. Add and edit a vehicle by hand, including pasting a source URL. Optional: if a URL is given, fetch the page server side and try to prefill title and price from Open Graph tags and JSON-LD only. If that fails, leave fields blank and say so. Respect robots.txt, honour a 5 second timeout, do not crawl beyond the single URL given.
2. Record a new price point for a vehicle at any time. Show a sparkline or a simple bar list of price history plus total change since first seen.
3. List view with filters: make, country, euro class, year range, mileage range, status. Sort by price, mileage, price per 1000 km.
4. Compare view: pick two to four vehicles, render a side by side table of every field plus a computed value score (price divided by remaining useful mileage, with the assumed end of life km configurable in .env).
5. A single command, npm run check, that re-fetches every vehicle with a source_url, records a new price_point when the parsed price differs, writes alert_events for changes and for anything untouched in 30 days, and prints a summary. No background scheduler, no email.
6. CSV import and export of vehicles so a spreadsheet stays the source of truth if I want.

Out of scope, do not build: messaging sellers, payments, user auth, public listing pages, scraping search result pages, translation, image hosting beyond storing one image URL string.

Config in .env: PORT, DB_PATH, DEFAULT_CURRENCY, END_OF_LIFE_KM. Commit a .env.example, never a .env.

Deliver: npm install then npm run dev serving on localhost, a seed script with 8 fake trucks, and a README with the three commands and a one paragraph note that this tracks listings found elsewhere and is not a marketplace.