The Problem I Wanted to Solve
Have you ever wondered why your perfectly crafted CV doesn't get you interviews? The answer often lies in Applicant Tracking Systems (ATS) - those invisible gatekeepers that scan your CV before a human ever sees it. Most ATS checkers are basic and don't give you real insights. I wanted to change that.
So I built a CV ATS Checker that actually helps you understand what's wrong with your CV and how to fix it. Think of it as having a smart friend who's an expert at getting past these systems.
What I Built
My app is like a smart CV doctor. You upload your CV (PDF or Word), tell it what job you're applying for, and it gives you:
- A score from 0-100 (like a grade for your CV)
- Specific problems it found
- Real tips to make it better
The Tech Stack I Chose
I went with React.js because it's like building with LEGO blocks - you can create reusable pieces and put them together easily. For styling, I used Tailwind CSS, which lets me make things look good without getting lost in CSS complexity.
The real magic comes from Google's Gemini AI. It's like having a very smart assistant who actually understands what makes a good CV. When you upload your CV, it reads through it like a human would and gives you personalized advice.
The Challenges I Faced
PDFs Were Tricky
The biggest headache was getting PDFs to work properly. Some PDFs are just scanned images (like taking a photo of a paper), and others have weird formatting. I spent hours making sure the app could handle all types of PDFs without crashing.
Here's what I learned: always have a backup plan. If the main way of reading a PDF fails, try another approach. It's like having multiple keys to open a door.
Making It Work on GitHub Pages
I wanted to host this for free, so I chose GitHub Pages. But React apps don't work there out of the box - they need special configuration. I had to learn about GitHub Actions (automated workflows) and how to make React work in a static hosting environment.
The trick was creating a workflow that automatically builds and deploys your app every time you make changes. It's like having a robot that rebuilds your house every time you redecorate.
How It Actually Works
Step 1. Upload Your CV
You drag and drop your CV or click to browse. The app supports PDFs and Word documents. I made sure it gives you clear feedback, like "CV loaded successfully," so you know it worked.
Step 2. Tell It About the Job
You enter the job title you're applying for. This is crucial because the AI needs to know what to look for. It's like telling a chef what dish you want them to make.
Step 3. Get Smart Analysis
The AI reads your CV and compares it to what the specific job needs. It's not just checking for keywords - it's understanding context, structure, and relevance.
The User Experience I Wanted
I wanted this to feel like talking to a helpful friend, not using some corporate software. So I added:
- Loading animations so you know something is happening
- Color-coded scores (green for good, yellow for okay, red for needs work)
- Clear explanations instead of technical jargon
- Helpful warnings like "This looks like a scanned document"
What I Learned Along the Way
Always Plan for Failure
Things will go wrong. PDFs will be corrupted, API calls will fail, and users will do unexpected things. Building robust error handling isn't glamorous, but it's what separates a good app from a frustrating one.
User Experience Matters
I could have made this a command-line tool, but people want something that looks good and feels intuitive. The glass morphism design (that frosted glass look) makes it feel modern and trustworthy.
AI Integration Isn't Magic
While Gemini AI is incredibly powerful, you still need to guide it. I had to write clear prompts and handle cases where the AI might give unexpected responses. It's like teaching someone very smart but who doesn't always understand context.
The Deployment Journey
Getting this live was its own adventure. I learned about:
- Environment variables (how to keep your API keys secret)
- GitHub Actions (automating the boring stuff)
- SPA routing (making sure links work properly)
- Build optimization (making the app load fast)
What Makes This Special
Most ATS checkers just count keywords. Mine actually understands your CV. It can tell if you're using the right language for the job, if your experience matches what they're looking for, and give you specific advice on how to improve.
It's also completely private - nothing gets stored on servers. Your CV is processed in your browser and then forgotten. In today's world of data breaches, that's important.
The Future
I'm already thinking about what's next:
- Multiple language support (because not everyone speaks English)
- CV comparison tools (test different versions)
- Industry-specific advice (what works for tech vs. marketing)
- Mobile app (because people check their phones more than computers)
Why I'm Sharing This
I built this because I was frustrated with existing tools. But I'm sharing the code because I believe in open source - when we share what we build, everyone gets better.
If you're a developer, you can see exactly how I solved problems. If you're a job seeker, you can use it for free. If you're curious about AI, you can see how it's not just science fiction - it's practical tools that make life easier.
Final Thoughts
Building this app taught me that the best software solves real problems in simple ways. It doesn't need to be complicated to be powerful. Sometimes the most elegant solution is just making something that works well and feels good to use.
The tech world often focuses on the next big thing, but there's real value in making everyday tasks easier. If my app helps even one person get a job they wouldn't have gotten otherwise, that's success.
Maybe it'll help you land your next job. Or maybe it'll inspire you to build something that solves a problem you care about. Either way, that's what makes coding worthwhile.