Chargeback Protection for Ecommerce Sellers

AI Prompts to Build This

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1. 1. Project Setup

   Build the weekend MVP of "SellerShield": it flags risky orders before they ship and drafts the evidence for a chargeback, for one Shopify store.
   
   Stack: Next.js (App Router), TypeScript, Tailwind, Supabase (Postgres, Row Level Security, Auth with email magic link), the Shopify Admin API for order webhooks, the Anthropic API for the dispute draft. Deploy on Vercel. A seller can also upload orders as a CSV, so you can test without a live store.
   
   Tables (Row Level Security on, scoped to the store's owner):
   - stores(id, user_id, shop_domain, access_token) access_token is read on the server only
   - orders(id, store_id, external_order_id, buyer_email, shipping_address, bill_to_address, total_cents, placed_at)
   - fraud_scores(id, order_id, score, signals jsonb, scored_at)
   - disputes(id, order_id, reason_code, filed_at, response_due_at, status, outcome) reason_code is one of not_received, not_as_described, fraudulent
   - evidence_items(id, dispute_id, type, label, url, extracted_text)
   
   Screens: /login, /orders (risk badges), /disputes/[id] (evidence and the draft).
   Env vars (names only): NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY (server only), SHOPIFY_API_KEY, SHOPIFY_API_SECRET, ANTHROPIC_API_KEY.
   
   Do not build: billing, plans or a performance fee, Amazon, eBay or WooCommerce, a job queue or Redis, automatic fulfillment holds, auto-submitting a dispute.
   Done when: npm run dev starts, you can sign in, and the five tables exist with Row Level Security on.

2. 2. Core Feature

   Build the one feature that proves SellerShield: score every order, then draft the dispute response from real evidence.
   1. A Shopify orders/create webhook (verify the HMAC signature) and a CSV upload both write rows to orders.
   2. Score each order from 0 to 100 in plain code, no model. Add points for: shipping and bill-to address mismatch, three or more orders on the same payment method or email in 7 days, several high-value orders to different addresses in one day, and a buyer account created in the last 24 hours. Save the score and the list of signals that fired to fraud_scores.
   3. /orders shows a badge for each order. A score over 70 reads "Review before shipping" and lists the signals. The badge carries the number, so color is not the only signal.
   4. A seller opens a dispute by hand: pick the order, the reason code and the response due date. Attach evidence items (tracking history, delivery confirmation, buyer messages, photos) as pasted text or a link.
   5. Send the order and the evidence items to the Anthropic API with a strict JSON schema { checklist: string[], rebuttal: string }. The checklist says which evidence this reason code usually needs and which of those the seller is missing. The rebuttal names each evidence item by its label.
   Rules: never invent a tracking number, date or quote that is not in the evidence. Never auto-submit; the seller copies the draft into their processor. Show the due date and warn when it is under 48 hours away.
   Empty state: with no orders, show the CSV upload and the expected columns.
   Done when: an uploaded test order with a mismatched address scores over 70 with its signals listed, and a dispute with three evidence items produces a rebuttal that names all three.

3. 3. Landing Page

   Build a one-page landing site for SellerShield, a chargeback shield for online sellers.
   Hero: "Stop losing chargebacks you should win." Sub: "Flag the risky order before you ship it, and get an evidence-backed response drafted the moment a dispute lands." One button: Get early access, which joins the waitlist.
   Sections: a before and after block with placeholders for your own win-rate and hours-saved numbers, how it works in four steps (connect, screen, respond, learn), a sample order card with a risk badge and the signals behind it, and an FAQ on data security, which stores work today (Shopify first) and why nothing is ever submitted without the seller's click.
   Waitlist: store the email in a waitlist table in Supabase. No other service.
   Style: Geist, a near-black background, one emerald accent, generous whitespace.
   Done when: the page renders on a phone and a submitted email appears in the waitlist table.

4. 4. Branding Package

   Use a design or image tool for this one. A coding agent cannot draw a logo.
   Brand for SellerShield: a wordmark and an icon that suggest a shield with a check cut into it, kept simple enough to read at 16 pixels.
   Colors: near-black, off-white and one emerald. Type: Geist, with tabular numbers for scores.
   Deliverables: wordmark, icon, three risk badges (clear, watch, review) that differ by shape and number as well as color, and one launch graphic.
   Done when: each deliverable is saved in one folder and the badges are distinguishable without color.