Can PromptIt generate prompts for Lovable?

Yes — PromptIt analyses your rough idea and builds a complete, structured prompt optimised for Lovable. It adds role, context, format constraints, and output specifications automatically.

Lovable 2.0by Lovable.dev

Lovable Prompt Generator

Stop getting 'close but wrong' from Lovable — prompt it like a pro.

Lovable generates full React applications from natural language prompts, using Claude under the hood. Prompts that specify UI component hierarchy, user authentication flows, data schema, and visual design consistently produce production-closer results than high-level descriptions.

Lovable builds full React + Supabase apps from prompts500K+ apps built on Lovable as of 2025Powered by Claude — benefits directly from structured prompt engineering

Source: Official Lovable prompting guide →

Lovable is the fastest way for non-technical founders to go from idea to working React app — but vague prompts reliably produce vague results. Lovable uses Claude to generate and iterate on full applications, which means prompt quality directly determines build quality. PromptIt structures your rough idea into a Lovable-ready prompt with explicit screens, components, user flows, and design specs — so you get the right app on the first generation.

✦ Generate Lovable prompts free See example ↓

What makes a great Lovable prompt?

Describe your app's data model explicitly: 'Users have a profile with name, avatar, and subscription tier. Posts belong to users and have title, body, and created_at' — Lovable uses this to set up Supabase correctly

Name your screens and what's on each one: 'Screen 1: /dashboard shows a list of the user's saved prompts with title, date, and a copy button' is 10x better than 'a dashboard'

Include auth flow details: 'Email + password auth via Supabase. After login, redirect to /dashboard. Unauthenticated users hitting /dashboard redirect to /login'

Specify component behaviour, not just appearance: 'The prompt card expands on click to show the full text, with a collapse button' — Lovable implements interactions when they're described

Before & after: how PromptIt improves your Lovable prompts

Added explicit data model (Supabase schema), named all screens with their content, described auth flow, and specified card interactions — giving Lovable a complete spec instead of a goal.

✗ Weak prompt

“Build me an app where users can save their AI prompts.”

✓ PromptIt-optimised

Build a prompt library web app. Stack: React + Tailwind + Supabase. Auth: Email + password via Supabase Auth. After login → /dashboard. Unauthenticated users → redirect to /login. Data model: - profiles: id, email, created_at - prompts: id, user_id (FK), title (text), body (text), tags (text[]), created_at Screens: 1. /login: email + password form, 'Sign in' button, 'Create account' link 2. /dashboard: grid of prompt cards (title, first 80 chars of body, date, copy button, delete button). 'New prompt' button top right. Search bar filters by title. 3. /prompt/new: form with title input, body textarea, tags input (comma-separated). 'Save' and 'Cancel' buttons. Design: white background, cards with subtle shadow, black CTAs, Inter font.

Ready-to-use Lovable prompt starters

SaaS App

Build a [app name] web app. Stack: React + Tailwind + Supabase. Auth: Email + password. After login → /dashboard. Data model: - [table 1]: [columns] - [table 2]: [columns with FK] Screens: 1. /login: [form fields + CTA] 2. /dashboard: [what's shown, interactions] 3. /[resource]/new: [form fields] Design: [style description].

Directory / Listing App

Build a [type] directory app. Stack: React + Tailwind + Supabase. Data: [entity] has [fields]. Public read, authenticated write. Screens: 1. Home: search bar + grid of [entity] cards (show: [fields]). Filter by [category]. 2. /[entity]/[id]: detail page showing all fields, [action button] 3. /submit: form to add new [entity] (fields: [fields]). Requires login. Design: [style].

User Dashboard

Build a user dashboard for [product]. Stack: React + Tailwind + Supabase. Auth: Email + password. Screens: 1. /dashboard: shows [user's data], summary stats: [stat 1], [stat 2] 2. /settings: update name, email, password. Danger zone: delete account. 3. /[feature]: [description of main feature screen] Sidebar nav: Dashboard, [Feature], Settings, Sign out Design: sidebar layout, white main area, gray sidebar.

Feedback / Form Tool

Build a [feedback type] collection tool. Stack: React + Tailwind + Supabase. Public form: [fields]. On submit → save to Supabase + show thank you message. Admin view (password protected): table of all submissions with [columns]. Export to CSV button. Design: [style]. Form should look trustworthy and professional.

Lovable prompting tips

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Write out your Supabase data model before anything else — table names, columns, and foreign keys give Lovable the schema it needs to wire things up correctly

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Name every screen with its route (/dashboard, /settings) and describe exactly what appears on it — don't say 'a profile page', say 'a profile page with editable name, avatar upload, and subscription status'

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Describe auth flows as redirect rules: 'Unauthenticated users hitting /dashboard redirect to /login' is clearer than 'handle auth'

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Specify component interactions: 'The card expands on click', 'The button shows a loading spinner while saving' — Lovable implements behaviour when you describe it

Stop writing weak Lovable prompts

PromptIt analyses your rough idea and builds a complete, structured prompt with role, context, constraints, and format — ready to paste into Lovable in seconds.

✦ Try PromptIt free — no card needed

Explore more

Browse all prompt templates →Prompt engineering guides →