AI Resume Analyzer & Cover Letter Generator

**Project Description**

**AI Resume Analyzer & Cover Letter Generator** – a web-based tool designed to help job seekers improve their resumes by comparing them with job descriptions, identifying missing skills, and creating tailored cover letters.

**Problem:**
A lot of job seekers apply for roles without really knowing if their resume matches what the company is looking for. Because of this, many resumes get filtered out by Applicant Tracking Systems (ATS) before a recruiter even sees them. On top of that, people often don’t know what’s missing in their resume, how to improve certain sections, or how to write a good cover letter for each job.

**Solution:**
This project offers a simple web platform where users first enter the job details, like the job description, required skills, and experience level, and then upload their resume in PDF or DOCX format. The system uses AI to analyze the resume against the job description, gives a match score, highlights missing keywords, and provides feedback on different sections of the resume. It also generates a cover letter that is specifically tailored to that job.

**Simplified cases:**

1. A student applying for a software engineering internship uploads their resume along with the job description. The tool points out missing skills like “React” or “REST API”, suggests improvements, generates report along with a relevant cover letter.

2. Someone applying to multiple jobs uses the tool to adjust their resume for each role. By comparing their resume with different job descriptions, they can quickly see gaps and generate customized cover letters for each application.

**References:**
https://www.jobscan.co/
https://resumeworded.com/

The issue provides no repository files, tests, or entry points to inspect. Start by reviewing the stated resume-upload, job-matching, scoring, feedback, and cover-letter requirements alongside the referenced examples; done would require a defined implementation scope and working web platform, but no acceptance criteria are given.

Written by the indexing model from the issue text.