The Resume Tailor

Resume Tailor uses Google Gemini to customize your resume for any job description. It automatically generates a personalized CV and populates application fields, saving you time and effort.

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Resume Tailor Project Story

Inspiration

What inspired you to create Resume Tailor?

Applying for jobs is often a tedious and frustrating process, and one of the most time-consuming tasks is constantly updating your resume to match each job description. Every job posting requires specific skills, keywords, and experiences to be highlighted, which can feel repetitive and inefficient. That frustration led me to create Resume Tailor — an extension that automates the process of tailoring your resume to match any job description using AI, so you don’t have to do it manually every time.

What it does

What problem does Resume Tailor solve, and how does it work?

Resume Tailor is a Chrome extension that uses Google Gemini AI to analyze job descriptions and automatically customize your resume to fit the application. The extension scans the job listing, extracts relevant keywords and skills, and updates your resume to match the job requirements. Additionally, it has an autofill feature that populates application fields automatically, saving users time and effort during the application process.

How we built it

What tools, technologies, and strategies did you use to develop Resume Tailor?

To build Resume Tailor, I used the following technologies:

  • Chrome Extension SDK: For creating the extension and handling browser interactions.
  • Google Gemini AI: For analyzing job descriptions and generating tailored resume content.
  • Google Built in APIs (Summary/Prompt): For summarizing the job into a few main points and creating a funny message to include in the cover letter for the hiring manager.
  • React: For building the user interface of the extension.
  • TypeScript: For adding type safety and improving code maintainability.
  • Material UI: For creating a modern, responsive design.

The extension works by analyzing a job listing page, using Google Gemini AI to extract the relevant details (such as job title, skills, and responsibilities), and dynamically updating your resume. I also implemented an autofill feature that grabs application fields from a job application page and populates them automatically with the information from your resume.

Challenges we ran into

What difficulties or obstacles did you face during development, and how did you overcome them?

One of the main challenges was working with the Chrome Extension SDK, particularly around storage and messaging between background scripts and content scripts. Chrome’s architecture required careful management of data between the different parts of the extension, which took some time to get right. Another challenge was integrating AI-driven content generation with the browser extension in a way that would work seamlessly and quickly for users. The output of some of the AI models proved to be inconsistent so at times the results were not what I expected. Despite these challenges, I managed to work through them by researching and testing different approaches for message passing and optimizing the AI integration.

Accomplishments that we're proud of

What are the highlights or achievements you are most proud of in this project?

I'm particularly proud of the autofill feature, which is a key part of the extension. While it's still partially functional, the fact that the AI can intelligently parse application fields from a webpage and generate the JavaScript commands needed to fill those fields is a huge achievement. It was exciting to see how Google Gemini AI could automate such a complex process. The idea of using a built in AI model directly in Chrome was also really nice. I'd love to see these added as standard browser APIs. Additionally, creating a Chrome extension that works seamlessly within the browser was a rewarding experience that helped me better understand how to integrate different web technologies.

What we learned

What were the key takeaways from building this project?

Building Resume Tailor taught me a lot about the Chrome Extension SDK, particularly around managing storage and ensuring smooth communication between background scripts and content scripts. I also gained hands-on experience with Google Gemini AI/ Built in APIs and its capabilities in extracting relevant data from job descriptions. On top of that, this project improved my skills in building browser extensions with React and TypeScript, especially in terms of performance optimization and maintaining clean, modular code.

What's next for Resume Tailor

What are the next steps or future plans for the project?

The next step for Resume Tailor is to launch the extension in the Chrome Web Store for public use. Once it’s live, I’ll continue to build out enhancements, such as improving the autofill feature and expanding AI capabilities for even more accurate resume customization. I also plan to add features like multiple resume templates and the ability to tailor cover letters. The goal is to make the job application process as efficient as possible for job seekers.

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