SkillSharp

SkillSharp - AI-Powered Skills Gap Analysis Platform Sharpen Your Skills. Advance Your Career. A comprehensive web application that analyzes your resume against job descriptions, discovers skill gaps, and provides personalized learning roadmaps with interactive SQL challenges and AI mentorship.

🚀 Quick Start Authentication For now, please use the hard login credentials:

Username/Email: rao305@purdue.edu Password: demo11 Prerequisites Node.js 18+ and npm Supabase account (or use demo mode) Installation & Setup Clone and Install

cd frontend/bdpafrontend-main npm install Environment Setup Create a .env.local file in the frontend/bdpafrontend-main directory:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key Start Development Server

cd frontend/bdpafrontend-main npm run dev Access the Application

Homepage: http://localhost:3000 Auth: http://localhost:3000/auth (use hard login credentials above) Admin Setup: http://localhost:3000/admin/seed 📋 Features Overview

Skills Analysis & Resume Parsing Upload PDF resume with automatic text extraction Manual skills entry with autocomplete Coursework and experience tracking Target industry selection
Job Description Analysis Select from predefined role templates (ML Engineer, Data Scientist, Full-Stack SWE, DevOps, etc.) Paste any job description for analysis Real-time multi-dimensional scoring Market demand analysis for missing skills
Comprehensive Scoring System The platform uses a sophisticated rule-based scoring algorithm across 6 dimensions:

Overall Score (Weighted): Combined score from all dimensions Alignment (35%): Semantic similarity between resume and job description using TF-IDF vectorization Readiness (25%): Percentage of required skills that you possess Impact (15%): Quantified achievements and project experience Potential (10%): Growth trajectory based on skills and coursework ATS (15%): Resume formatting and keyword optimization quality Polish: Professional presentation and completeness

Interactive Dashboard with Analytics The dashboard provides comprehensive metrics and visualizations:

KPI Cards Average Overall Score: Mean score across all analyses Total Analyses: Number of job analyses performed Average Alignment: Mean alignment score Average Readiness: Mean readiness percentage Interactive Charts Score Trend Over Time (Line Chart)

Shows how your overall score changes across multiple analyses X-axis: Analysis date Y-axis: Overall score (0-100) Helps track improvement over time Subscore Radar Chart

Visualizes all 6 scoring dimensions in a radar/spider chart Each axis represents: Alignment, Readiness, Impact, Potential, ATS, Polish Shows strengths and weaknesses at a glance Readiness Distribution (Histogram)

Bar chart showing distribution of readiness scores X-axis: Readiness percentage ranges (0-20%, 20-40%, etc.) Y-axis: Number of analyses in each range Helps identify consistency in skill coverage Hot Skills Over Time (Line Chart)

Tracks which skills are most in-demand across your analyses Shows market trends for missing skills Multiple lines for different skills Helps prioritize learning based on market demand Top Missing Skills (Bar Chart)

Horizontal bar chart of most frequently missing skills Sorted by frequency and market demand Shows which skills appear most often in job descriptions you're targeting Role Coverage (Pie Chart)

Shows distribution of analyses by role type Helps identify which roles you analyze most Visual representation of your career focus areas Dashboard Filters Role Filter: Filter analyses by specific role (All, ML Engineer, Data Scientist, etc.) Date Filter: Filter by time period (All Time, Last 7 Days, Last 30 Days, Last 90 Days) Clickable Table: Click any analysis row to view detailed results

Learning Hub The Learning Hub is your personalized learning center with multiple features:

14-Day Learning Plan Auto-generated personalized learning roadmap Tasks organized by day with checkboxes Based on your skill gaps and target roles Progress tracking (In Progress, Completed) Saved Resources Curated learning resources from all your analyses Links to tutorials, courses, and documentation Organized by skill category Easy access to recommended materials SQL Learning Hub with AI Mentor A comprehensive SQL learning platform with interactive challenges:

5 Progressive Levels:

Foundations (Level 1): SELECT, WHERE, ORDER BY, filtering, NULL handling Intermediate (Level 2): JOINs, GROUP BY, HAVING, aggregate functions Advanced (Level 3): CTEs, Window Functions, subqueries, CASE statements Real-world Scenarios (Level 4): Dashboards, transactions, complex queries Capstone Project (Level 5): End-to-end analytics systems Each Challenge Includes:

Industry Context: Real-world business scenarios explaining why the skill matters Business Value: How the query helps organizations make decisions Sample Data: Actual table data to work with Database Schema: Complete table structures Expected Output: What the result should look like Learning Resources: YouTube tutorials and articles for each concept Progressive Hints: Multiple levels of hints without giving away solutions AI Mentor Chatbot:

Trigger Words: Ask for "help", "hint", "explain the problem", "guide me" Context-Aware Responses: AI understands your current challenge and provides relevant assistance Query Analysis: Get explanations for your SQL queries Step-by-Step Guidance: Walkthroughs for complex problems Markdown Support: Formatted responses with code blocks and lists Interactive Features:

Query Editor: Write and test SQL queries Validate Solution: Check if your query is correct Explain Query: Get line-by-line explanations Debug: Find syntax and logical errors Get Hint: Progressive hints that don't reveal the solution

Market Analysis Engine The platform includes a sophisticated market analysis engine that:

Prioritizes Skills: Ranks missing skills by market demand and job requirement level Industry Context: Provides real-world explanations for why each skill matters Business Value: Explains how skills help organizations Personalized Explanations: Tailored recommendations based on your existing skills Market Demand Data: Shows number of job opportunities for each skill

Results & Recommendations After each analysis, you receive:

Detailed Scores: Breakdown of all 6 scoring dimensions Strengths: What you're doing well Areas to Improve: Specific gaps identified Prioritized Missing Skills: Required skills (must-have) Preferred skills (nice-to-have) Market demand numbers for each Learning Resources: 1-2 curated resources per missing skill Learning Path Recommendation: Suggested order for learning new skills 🏗 Technical Architecture Tech Stack Frontend Framework: Next.js 13 (App Router) Language: TypeScript Styling: Tailwind CSS + shadcn/ui components Database: Supabase (PostgreSQL) with Row Level Security Authentication: Supabase Auth (email/password) Charts & Analytics: Recharts State Management: Zustand Forms: React Hook Form + Zod validation Core Algorithms TF-IDF Vectorization

Converts resume and job description text into numerical vectors Identifies important keywords and phrases Used for semantic similarity calculation Cosine Similarity

Measures alignment between resume and job description Returns score between 0-1 Accounts for keyword frequency and importance Market Analysis Engine

Prioritizes skills by market demand Considers job requirement levels (required vs preferred) Provides industry-specific context Gap Analysis Algorithm

Identifies missing skills from job description Categorizes by severity (critical, important, beneficial) Suggests learning order based on dependencies Scoring Algorithm

Multi-dimensional weighted scoring Normalizes scores across different metrics Provides actionable feedback Project Structure bdpa-main/ ├── frontend/bdpafrontend-main/ # Main application │ ├── app/ # Next.js 13 App Router │ │ ├── api/ # Backend API routes │ │ │ ├── analyze/ # Analysis endpoint │ │ │ ├── profile/ # User profile management │ │ │ ├── sql-instructor/# SQL Learning Hub API │ │ │ └── seed/ # Database seeding │ │ ├── auth/ # Authentication pages │ │ ├── analyze/ # Job analysis interface │ │ ├── dashboard/ # Analytics dashboard │ │ ├── learn/ # Learning Hub (14-day plan + SQL) │ │ ├── onboarding/ # Profile setup │ │ ├── results/ # Analysis results │ │ └── profile/ # Profile management │ ├── components/ # React components │ │ ├── ui/ # shadcn/ui components │ │ ├── results/ # Results display components │ │ └── learn/ # Learning Hub components │ ├── lib/ # Core libraries │ │ ├── ml-engine.ts # ML analysis algorithms │ │ ├── scoring.ts # Scoring system │ │ ├── market-analysis.ts # Market analysis engine │ │ ├── sql-instructor.ts # SQL Learning Hub logic │ │ ├── gap-analysis.ts # Gap identification │ │ └── resource-engine.ts # Learning recommendations │ └── README.md # Detailed frontend documentation ├── analysis/ # Analysis scripts ├── 2025 Job Market/ # Job market datasets └── Kaggle Datasets/ # ML-ready datasets 📊 Understanding the Graphs Dashboard Charts Explained

Score Trend Over Time What it shows: Your overall analysis scores plotted chronologically How to read:

Upward trend = improving fit over time Flat line = consistent performance Downward trend = may need to adjust target roles or skills Use case: Track long-term improvement and identify when you made skill gains

Subscore Radar Chart What it shows: All 6 scoring dimensions in one view How to read:

Larger area = better overall fit Each axis represents one dimension Asymmetric shape = strengths and weaknesses Use case: Quick visual assessment of which areas need work

Readiness Distribution What it shows: How often you meet different percentages of required skills How to read:

Bars on the right (80-100%) = strong skill coverage Bars on the left (0-40%) = significant gaps Tall bars = common pattern in your analyses Use case: Understand consistency of your skill coverage

Hot Skills Over Time What it shows: Market demand trends for skills you're missing How to read:

Rising lines = increasing demand Multiple skills = shows which are trending Y-axis = normalized demand score Use case: Prioritize learning based on market trends

Top Missing Skills What it shows: Most frequently missing skills across all analyses How to read:

Longer bars = appear in more job descriptions Sorted by frequency and market demand Shows which skills to learn first Use case: Identify the most important skills to acquire

Role Coverage What it shows: Distribution of analyses by role type How to read:

Larger slices = roles you analyze most Multiple small slices = exploring different paths Single large slice = focused on one role type Use case: Understand your career exploration patterns 🔄 User Flow

Landing Page (/) ↓
Authentication (/auth) - Use hard login: rao305@purdue.edu / demo11 ↓
Onboarding (/onboarding)
- Upload resume OR enter skills manually
- Add coursework and experience
- Select target industry ↓
Dashboard (/dashboard)
- View analytics and trends
- See past analyses ↓
Analyze (/analyze)
- Select role template
- Paste job description
- Click "Analyze Fit" ↓
Results (/results/:id)
- View detailed scores
- See missing skills
- Get learning recommendations ↓
Learning Hub (/learn)
- 14-day learning plan
- SQL challenges with AI mentor
- Saved resources 🎯 Key Pages / - Welcome page with feature overview /auth - Email/password authentication (use hard login credentials) /onboarding - Profile setup (resume upload or manual entry) /dashboard - Analytics dashboard with charts and metrics /analyze - Role analysis with job description input /results/:id - Detailed analysis results with scores /learn - Learning Hub (14-day plan + SQL Learning Hub) /profile - Profile management and editing /admin/seed - Database seeding (admin only) 🛠 API Endpoints POST /api/analyze - Run skill gap analysis GET/POST /api/profile - User profile management GET /api/roles - Available role templates GET /api/analyses - User's analysis history POST /api/seed - Database seeding (admin) POST /api/upload - Resume upload and parsing GET /api/sql-instructor - SQL Learning Hub data POST /api/sql-instructor - SQL query validation and AI mentor chat 📚 Database Schema The database includes the following tables:

profiles - User profiles with skills, coursework, and experience roles - Predefined role templates (ML Engineer, Data Scientist, etc.) resources - Learning resources mapped to skills analyses - Saved analysis results with scores and recommendations All tables use Row Level Security (RLS) to ensure users can only access their own data.

🚀 Production Build & Deployment Local Production Build cd frontend/bdpafrontend-main npm run build npm run start Netlify Deployment The project includes Netlify configuration files for easy deployment:

Connect your GitHub repository to Netlify

Build Settings (should auto-detect):

Base directory: frontend/bdpafrontend-main Build command: npm install && npm run build Publish directory: .next Node version: 18 Environment Variables: Add these in Netlify dashboard → Site settings → Environment variables:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key Netlify Plugin: The @netlify/plugin-nextjs plugin is configured in netlify.toml and will be automatically installed during build.

Deploy: Click "Deploy site" and Netlify will handle the rest.

Note: The Netlify Next.js plugin automatically handles routing for Next.js 13 App Router, so no manual redirects are needed.

🔒 Security Features Row Level Security (RLS) on all database tables Secure authentication via Supabase Auth No API keys or secrets exposed client-side Password reset uses Supabase's secure flow Protected routes with automatic redirection 🐛 Troubleshooting Common Issues Port already in use: Next.js will auto-assign a new port (3001, 3002, etc.)

Supabase connection errors:

Check .env.local has correct credentials Verify database schema is applied For demo, placeholder credentials work for UI testing Build errors:

npm run typecheck # Check TypeScript errors npm run lint # Check linting issues Empty dashboard: Run an analysis first or visit /admin/seed to populate sample data

Auth not working:

Use the hard login credentials: rao305@purdue.edu / demo11 Check that your Supabase project has email auth enabled 📝 Development Commands cd frontend/bdpafrontend-main npm run dev # Start development server npm run build # Build for production npm run start # Start production server npm run lint # Run ESLint npm run typecheck # TypeScript checking 🎓 Learning Resources The platform provides curated learning resources including:

YouTube Tutorials: Video lessons for each SQL concept Interactive Courses: Step-by-step learning paths Documentation: Official documentation links Practice Challenges: Real-world SQL problems with solutions 🔮 Future Enhancements Additional programming language learning hubs Real-time collaboration features Advanced ML model training Integration with learning platforms Mobile app support 📄 License MIT

🤝 Support For issues or questions, please open an issue on GitHub or contact the development team.

SkillSharp - Sharpen Your Skills. Advance Your Career.