JD Assistent: Intelligent Resume Optimization System Based on Multi-Agent Workflow

JD Assistent is an intelligent resume optimization application built with FastAPI + Vue 3. It core uses a multi-agent workflow architecture, which can deeply parse job descriptions, extract key skills, intelligently rewrite resume content, and go through an audit loop. Finally, it outputs a customized resume in Word format to help job seekers accurately match their target positions and increase the probability of their resumes passing ATS screening.

In the highly competitive job market, the resume is the first threshold to get an interview opportunity. However, many job seekers have their resumes filtered out by screening systems because they submit the same resume to different positions with insufficient matching. JD Assistent aims to solve this pain point, and its core capabilities include:

• Deeply parse job descriptions and extract key skill points
• Analyze core competency requirements of target positions
• Intelligently rewrite resume content to match needs
• Ensure output quality through an audit loop
• Export professional Word documents The system adopts the "one resume per position" strategy, significantly improving ATS pass rates.

JD Assistent adopts a front-end and back-end separation architecture:

Front-end Layer (Vue 3)

Provides a responsive web interface, supporting user login/account management, resume task creation and management, real-time progress tracking, result preview and export, task history query, and multi-theme switching.

Back-end Layer (FastAPI)

High-performance asynchronous API service, responsible for user authentication and permission management, resume optimization task processing, admin backend interfaces, and system health checks.

Task Flow Engine

Supports two operation modes: Local Mode (local sequential execution) and Asynchronous Mode (Redis-based distributed task queue, supporting concurrency).

The core competitiveness of JD Assistent lies in its multi-agent collaboration process, which is divided into five stages:

Job Description Parsing

Identify hard skills (programming languages, tools, etc.), soft skill keywords, experience years/educational requirements, and bonus items.

Resume Content Mapping

Match the original resume with position requirements, identify relevant experience, skill gaps, and project relevance.

Intelligent Content Rewriting

Optimize skill descriptions with position keywords, reorganize project experience expressions, highlight relevant achievements, and adjust industry terminology.

Quality Audit Loop

Check keyword coverage, logical consistency, information authenticity, and readability.

Format Export

Output standard-formatted, editable Word documents compatible with mainstream recruitment platforms.

Functional Features

• Real-time Task Tracking: View active steps, completion status, task operation status, and result notifications.
• User Account and Task History: Secure login, personal space isolation, historical task archive retrieval, multi-resume version management.
• Flexible Export Options: Currently supports Word format; PDF and other formats will be added in the future.

Usage Flow

1. Download and install the latest Windows version; 2. Log in/register an account; 3. Create a task and upload your resume; 4. Paste the job description;5. Start the workflow;6. Preview the result and export Word.

Usage Suggestions

Ensure the JD is complete, use one resume per position, audit before export, include the position name in the file name, and keep the original resume.

Application Value

• Job Seekers: Save modification time, improve matching degree, learn JD adaptation skills, and establish a multi-version management system.
• Recruitment Process: Reduce screening noise, help HR quickly identify candidates, and promote accurate matching.
• Technical Demonstration: Show multi-agent workflow applications, verify the maturity of the FastAPI+Vue3 tech stack, and provide a reference architecture for document generation applications.

Future Outlook

Plans to support more export formats, integrate recruitment platform APIs, introduce semantic matching algorithms, optimize for multiple languages, and add resume scoring and diagnosis functions.