amitkumardemo/edgecareer — explained in plain English
Analysis updated 2026-05-18
Get AI-generated job recommendations and industry insights.
Generate a cover letter automatically from just a job role.
Practice interviews with AI feedback that points out mistakes.
Self-host a full career-coaching app for a community or contributor project.
| amitkumardemo/edgecareer | polymarket-sports/polymarket-trading-bot | cobusgreyling/loop-engineering | |
|---|---|---|---|
| Stars | 142 | 142 | 141 |
| Language | JavaScript | JavaScript | JavaScript |
| Setup difficulty | moderate | hard | easy |
| Complexity | 3/5 | 4/5 | 3/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires NeonDB, Clerk, and Gemini API keys before the app will run.
EdgeCareer is a full stack web application described as an AI powered career coach, built to give job seekers personalized recommendations, resume feedback, and interview practice. It is built with React and Next.js on the frontend, styled with Tailwind CSS and the Shadcn UI component library, and uses NeonDB as its database with Prisma as the tool that manages database access. User accounts and login are handled through Clerk, and background tasks such as generating AI content run through a service called Inngest. The actual AI features, including resume review, a cover letter generator, and interview preparation, are powered by Google's Gemini API. According to its feature list, the application can produce real time industry insights, generate a cover letter from just a job role, run a simulated AI interview that points out mistakes and offers suggestions, and present all of this through an interactive, modern interface. It appears to be an actively developed community project that welcomes outside contributors across frontend, backend, AI, and design work, and it is explicitly connected to a program called GirlScript Summer of Code, with a note asking contributors to install a specific VS Code extension for their pull requests to be reviewed and counted toward that program. Running the project locally requires cloning the repository, installing dependencies with npm, setting up a handful of environment variables covering the database connection, Clerk authentication keys, and a Gemini API key, then generating the Prisma database schema before starting the development server. A Docker based setup is also documented as an alternative, building a container image with the required environment variables passed in at build time and then running it. The project is released under the MIT license, a permissive license that allows free use, modification, and redistribution, including for commercial purposes, as long as the original license text is kept. A live demo link is provided in the README for anyone who wants to try the application without setting it up themselves.
A full-stack AI career coach web app offering job recommendations, resume review, cover letters, and mock interviews, built with Next.js and Gemini.
Mainly JavaScript. The stack also includes React, Next.js, Tailwind CSS.
Use freely for any purpose, including commercial use, as long as you keep the copyright and license notice.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.