AI Prompt Optimization Service for Marketers

AI Prompts to Build This

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1. 1. Project Setup

   Build the weekend MVP of "PromptPro": score a marketing team's real prompts in a free audit, then keep the fixed ones in a brand-voice prompt library.
   
   Stack: Next.js (App Router), TypeScript, Tailwind, Supabase (Postgres, Row Level Security, Auth with email magic link), Claude (Anthropic API) for the scoring. The audit form is public. Deploy on Vercel.
   
   Tables (Row Level Security on: the library is private to its owner, the audit table takes public inserts and no public reads):
   - brands(id, user_id, name, voice_rules, forbidden_claims, icp_summary)
   - prompt_kits(id, brand_id, channel, campaign_type)
   - prompts(id, kit_id, title, body, version, job)  where job is one of ads, email, landing, social, qa
   - audits(id, user_id, submission jsonb, scores jsonb, report_markdown, created_at)
   
   Screens: /audit (public form), /library, /login.
   Env vars (names only): NEXT_PUBLIC_SUPABASE_URL, NEXT_PUBLIC_SUPABASE_ANON_KEY, SUPABASE_SERVICE_ROLE_KEY (server only), ANTHROPIC_API_KEY.
   
   Do not build: billing, plans or workshop SKUs, the eval runner across models, Notion export, emailing the report, stale-prompt digests, an admin area.
   Done when: npm run dev starts, the public audit form loads, you can sign in to the library, and the four tables exist with Row Level Security on.

2. 2. Core Feature

   Build the one feature that proves PromptPro: a prompt audit that scores what a team actually uses.
   1. POST /api/audit takes an optional brand URL, 10 prompts (title, body, sample_output), the stated channels and a one-sentence offer.
   2. For each prompt, ask Claude to score it from 0 to 5 on voice specificity, ICP presence, conversion job (what action, what proof), claim safety (unverified superlatives), channel fit, and reuse (variables against hardcoded product names). Return strict JSON.
   3. Build a 3-page Markdown report: an executive summary, a per-prompt table, the top five failures, and a recommended kit map (a voice system, three campaign kits and a QA checklist). Show it on screen and save it to audits.
   4. Library: kits grouped by channel, a copy button, version history, and a "duplicate for new campaign" action that forces offer, ICP and date fields before it copies.
   Rules: do not rewrite their whole library in the audit. The audit finds the problems and the rewrite is the paid work. Save the raw submission for follow-up only.
   Empty state: an empty library shows the audit link and one sample kit.
   Done when: ten pasted prompts return scores and a report, scoring the same fixture twice gives the same shape of result, and duplicating a prompt asks for offer, ICP and date first.

3. 3. Landing Page

   Build a one-page landing site for PromptPro, custom prompt libraries for marketing teams.
   Headline: "Your team does not have a prompting problem. It has a context problem." Sub: "Custom prompt libraries: brand voice, campaigns, conversion. The audit is free." One button: Get the prompt audit, which links to /audit.
   Sections: a short story of a team whose prompts drifted off-brand, how it works in four steps (prompt audit, build the brand library, workshop and install, retain and measure), a sample audit score card, and a contrast with generic prompt tools and agencies.
   Voice: plain, strategic and a little dry.
   Done when: the page renders on a phone and the button opens the audit form.

4. 4. Branding Package

   Use a design or image tool for this one. A coding agent cannot draw a logo.
   Brand for PromptPro: a wordmark and an icon that suggest a bookmark inside a speech bubble.
   Colors: off-white, near-black and one aubergine accent. Type: Geist for the interface and a mono for prompt text.
   Deliverables: wordmark, icon, an audit score-card style, and one launch graphic.
   Done when: each deliverable is saved in one folder and the icon reads at 32 px.