LinkedIn Profile Coach AI

An AI-powered tool that analyzes LinkedIn profiles and helps users improve how they present themselves professionally. Built for students and early-career professionals who want to stand out.

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About

Many students and early-career professionals struggle with presenting their experience clearly, structuring their LinkedIn profile effectively, and knowing what skills or certifications to add. This tool bridges that gap by acting as a LinkedIn profile coach powered by AI.

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Features

Profile Analysis

Analyzes your LinkedIn profile and generates a structured report covering:

• Headline quality
• About section effectiveness
• Experience improvement suggestions
• Skills and certifications recommendations
• Featured section ideas
• Banner / visual branding feedback
• Overall profile completeness score

Step-by-Step Improvement Plan

Generates a clear, prioritized action plan — for example:

1. Rewrite your headline to reflect your target role
2. Add a compelling About section
3. Expand experience descriptions with measurable impact

Career-Specific Suggestions

Detects your likely career focus and surfaces relevant recommendations, including LinkedIn Learning certifications, key technical skills, and portfolio or project ideas. Supported areas include:

• Cybersecurity
• Software Engineering
• Data Science
• Business Analytics
• Marketing

Improved Profile Generator

Automatically rewrites your:

• Headline
• About section
• Experience descriptions
• Featured section
• Skills list
• Banner suggestion with a ready-to-use AI image generation prompt

Generated content can be copied directly into LinkedIn.

AI Chat Assistant

An interactive coach for follow-up questions after your analysis. Example questions:

• How can I improve my experience section?
• What cybersecurity certifications should I add?
• How should I present my projects?

Resume Integration (optional)

Paste your resume alongside your LinkedIn data to improve analysis accuracy. The AI will cross-reference both to surface missing skills, additional experience details, and projects worth showcasing.

LinkedIn Data Export Support

For the most accurate results, import your LinkedIn data archive instead of copying text manually. The tool reads your exported CSV files automatically (see Recommended Workflow below).

Saved Reports & Cached Profiles

• Generated reports are saved as .md files to the output/ folder with timestamped filenames (e.g. linkedin_profile_report_2025-03-12_14-30-00.md)
• Your last profile input is cached in cache/ so you don't need to re-paste it on every run

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Recommended Workflow (Start Here)

Using your LinkedIn data export produces significantly better results than pasting text manually.

Step 1 — Download Your LinkedIn Data

Go to LinkedIn → Settings & Privacy → Data Privacy → Get a copy of your data, then select Download larger data archive. LinkedIn will email you a ZIP file.

Step 2 — Extract the Archive

Right-click the ZIP → Extract All. Inside, you should see files like:

Profile.csv
Positions.csv
Education.csv
Skills.csv

Step 3 — Run the Program in VS Code

Open the project in VS Code, launch a terminal (Terminal → New Terminal), and run:

python main.py

When prompted, choose option 2) Use LinkedIn data export folder and paste the path to your extracted folder:

C:\Users\YourName\Downloads\LinkedInData

Prefer a quick start? You can choose option 1) Paste LinkedIn profile text instead — just note that the export method gives more complete results.

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Installation & Setup

1. Prerequisites

Install the following if you haven't already:

• Python 3.10+ — make sure to check Add Python to PATH during installation
• Visual Studio Code (recommended)

Verify Python is installed:

python --version

2. Clone the Repository

git clone https://github.com/YOUR_USERNAME/LinkedIn-Profile-AI.git
cd LinkedIn-Profile-AI

Or download the ZIP from GitHub: Code → Download ZIP, then extract it.

3. Install Dependencies

pip install -r requirements.txt

4. Configure Your API Key

This project uses a .env file to securely store your Gemini API key.

Rename the example file:

.env.example  →  .env

Then open .env and add your key:

GEMINI_API_KEY=your_api_key_here
GEMINI_MODEL=gemini-2.5-flash

Get a free Gemini API key at https://ai.google.dev.

5. Run the Program

python main.py

Follow the prompts to select your input method, optionally add your resume, and generate your analysis.

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Example Workflow

Run program
    ↓
Choose input method
    1) Paste LinkedIn text
    2) LinkedIn data export folder
    ↓
(Optional) Paste resume text
    ↓
AI analyzes your profile
    ↓
Receive full report + improvement plan
    ↓
Choose next action:
    - Generate rewritten sections
    - Chat with AI coach
    - Save report

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Project Structure

LinkedIn-Profile-AI/
│
├── main.py
├── requirements.txt
├── README.md
├── .env.example
│
├── src/
│   ├── analyzer.py
│   ├── gemini_client.py
│   ├── linkedin_parser.py
│   ├── post_analysis.py
│   └── report_generator.py
│
├── my_results/      # Real before/after results from testing on my own profile
├── output/          # Generated reports saved here
└── cache/           # Cached profile data

My Results

The my_results/ folder contains real output from running this tool on my own LinkedIn profile, including:

• Saved analysis reports and improvement plans generated by the AI
• A PowerPoint presentation with before and after screenshots of my LinkedIn profile showing the improvements made

This gives a concrete example of what the tool produces and how much a profile can improve with the right guidance.

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Technologies Used

• Python
• Google Gemini API
• CSV parsing
• CLI interface
• Prompt engineering

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Planned Features

• GUI interface
• Resume file upload (PDF/DOCX)
• Profile comparison mode
• LinkedIn banner generator
• Web application deployment

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License

MIT License

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Author

Robbie Karas
Computer Information Systems student at James Madison University
Interests: Cybersecurity, AI tools, and practical automation projects