I've created a Notion-style landing page for your Job Fit Scoring App with a clean, minimalist design. The page includes:

1. A header with navigation
2. A hero section explaining the app's purpose

3. A features section highlighting the three main functionalities:

   • Score: 1-100 on job fit
   • Explanations for the scoring
   • Suggested interview questions
4. A "How It Works" section showing the simple 3-step process

5. A demo section that shows a sample candidate evaluation with:

   • Overall score (78/100)
   • Detailed explanation of the score
   • Strengths and improvement areas
   • Suggested interview questions based on the resume

Since you mentioned not having access to OpenAI's API, I've implemented this as a static solution that demonstrates how the app would work with pre-filled sample data. This approach allows you to showcase the concept without requiring AI integration.

You could later enhance this with:

1. A simple rule-based scoring system using keyword matching
2. Resume parsing libraries like resume-parser or pdf.js
3. Pre-written explanation templates based on score ranges
4. A database of common interview questions by job role

This gives you a starting point that you can expand as your resources allow, while still providing value to recruiters with the static implementation.

I've created the functionality pages for your JobFit Scoring App, including:

1. Login Page (/login/page.tsx)

   • Email and password fields
   • Remember me checkbox
   • Forgot password link
   • Sign up link for new users
   • Password visibility toggle

2. Dashboard Page (/dashboard/page.tsx)

   • Protected route (requires login)
   • Sidebar navigation
   • Resume upload functionality
   • Job description input
   • Analysis submission form

3. Results Component (components/job-fit-results.tsx)

   • Displays the job fit score (78/100)

   • Tabbed interface with:

     • Score explanation
     • Strengths and gaps analysis
     • Suggested interview questions
   • Download and share options

4. Authentication Protection (middleware.ts)

   • Redirects unauthenticated users to the login page
   • Redirects authenticated users away from public pages

For this static implementation, I've used client-side authentication with localStorage to simulate the login process. The app demonstrates the complete user flow:

1. User logs in
2. User uploads a resume and enters a job description
3. User submits for analysis
4. User receives detailed job fit results

When you're ready to implement a real backend, you can:

1. Replace the localStorage authentication with a proper auth system
2. Connect the resume upload to a file storage service
3. Implement the actual scoring algorithm (either with AI or rule-based)

The UI is fully functional and provides a great demonstration of how the app would work in production.