Inspiration
Jobagotchi was created to make the job search process safer, clearer, and more supportive for students and early-career job seekers. It is a browser extension that analyzes job listings in real time, flags potentially suspicious or low-quality postings, and provides a simple trust score so users can make quicker, more confident decisions. Alongside this, it delivers daily motivational messages to help users stay consistent and encouraged throughout their job search journey.
What it does
Jobagotchi is a browser extension that analyzes job postings in real time while users browse platforms like LinkedIn. It evaluates listings for signs of authenticity or risk, flags potentially suspicious or low-quality jobs, and provides a simple trust score to help users make faster, more confident decisions. Alongside this, it also delivers daily motivational messages to support users emotionally throughout their job search journey.
How we built it
We built Jobagotchi as a browser extension using JavaScript, HTML, and CSS. It uses content scripts to extract job post data directly from web pages, then processes that information through a rule-based analysis system to assess job quality and legitimacy. We also built supporting modules for storage, UI rendering, and background processing to ensure the extension runs smoothly across different pages and sessions.
Challenges we ran into
One of the biggest challenges was designing a system that could accurately flag suspicious job posts without incorrectly labeling legitimate opportunities. We had to fine-tune our detection rules through multiple iterations and test on real-world job listings. Another challenge was handling different website structures and ensuring consistent data extraction across platforms.
Accomplishments that we're proud of
We are proud of building a working end-to-end browser extension that combines both technical functionality and user empathy. Successfully integrating real-time job analysis with a clean, user-friendly interface was a major milestone for us. We are also proud that the product not only focuses on safety but also supports users emotionally through motivation.
What we learned
Through this project, we learned how to design and build browser extensions, work with content scripts, and process real-time web data. We also strengthened our understanding of rule-based systems and UI integration. Most importantly, we learned how to balance technical problem-solving with user empathy to create a meaningful product.
What's next for jobagotchi
Next, we plan to improve the accuracy of our job analysis system using more advanced AI/ML techniques and expand support to more job platforms beyond LinkedIn. We also want to enhance personalization in motivational messages and potentially add features like resume feedback and application tracking to make Jobagotchi a complete career companion.
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