AI Job Search - An open-source AI job search framework that automatically matches and searches for jobs.

What is AI Job Search?

AI Job Search is an open-source AI job search framework based on Claude Code./setupEstablish detailed professional files./scrapeIntelligent assessment of job matching degree/applyThe framework initiates a dual-agent workflow of "drafting-reviewing," automatically generating customized LaTeX resumes and cover letters. It emphasizes that the depth of the profile determines the quality of the output, supports career path discovery, and is adaptable to recruitment platforms in different regions.

The main functions of AI Job Search

• Intelligent Archive Creation: Automatically generate structured career profiles covering educational background, skills, behavioral assessments, and career goals through interactive interviews or by importing existing resumes.
• Job matching and searchIt automatically captures job information from multiple platforms and intelligently scores them based on dimensions such as skills, experience, and cultural fit, then recommends the most suitable job opportunities after deduplication.
• Dual Agent Application Material GenerationIt uses a "draft-review" dual-agent workflow to analyze job requirements and automatically generate highly customized LaTeX resumes and cover letters that have been fact-checked.
• Interview preparation assistanceIt automatically generates a STAR behavioral interview case library based on real personal experiences, and provides a structured interview response framework and skills guidance.
• Career Path ExplorationBy deeply analyzing transferable skills and historical work patterns, it intelligently recommends cross-industry or emerging career opportunities that users may not have considered.
• Salary benchmarkIt supports integration with external salary datasets for market-level analysis, providing data reference for salary negotiations.

How to use AI Job Search

• Environmental preparationInstall Claude Code CLI, Python 3.10+, Bun and LaTeX distribution (TeX Live or MiKTeX).
• Fork and clone the repository:gh repo fork MadsLorentzen/ai-job-search --clone。
• Install search toolNavigate to the CLI directory of each job platform (e.g., jobindex-search/cli) and run the command. bun install。
• Establish personal files:run claude Enter the CLI and execute /setup Commands allow users to fill in their background, skills, and career goals through interactive interviews or by importing existing resumes.
• Search job:implement /scrape Automatically capture job postings from multiple platforms and assess their match.
• Apply for position:implement /apply <职位链接> Alternatively, paste the job description and initiate a dual-agent workflow to generate a customized resume and cover letter.

The core advantages of AI Job Search

• Dual-agency quality assuranceWe employ a dual-agency structure of "drafting-reviewing". After the drafting agent generates the materials, the agent independently researches the company's background and conducts a critical evaluation to ensure that the content is professional and authentic, and to prevent fabricated experiences.
• Authenticity verification mechanismAll application materials must be strictly verified against the user's real profile. The system will never fabricate skills or experience, ensuring the integrity and verifiability of job application materials.
• Archive depth drivingOutput quality directly depends on the level of detail in the input profile. Detailed job descriptions (including specific projects, tools, and quantifiable results) can generate highly accurate and customized content, avoiding generic, template-based applications.
• Career path discoveryBy analyzing transferable skills and complete career history, it intelligently recommends cross-industry opportunities or emerging role combinations that users may not have considered, thus broadening their job search horizons.
• Professional-grade document outputAutomatically generates LaTeX format resumes and cover letters with professional and aesthetically pleasing layout. Supports custom templates to directly meet the requirements of formal job application scenarios.

AI Job Search project address

• GitHub repositoryhttps://github.com/MadsLorentzen/ai-job-search

Comparison of AI Job Search with similar competitors

Comparison Dimensions	AI Job Search	LoopCV	Teal
Product Positioning	Open source intelligent job search framework	Fully Automated Batch Application Platform	Job Search Tracking and Optimization Platform
Technical Architecture	A native framework based on Claude Code CLI	SaaS cloud platform	SaaS cloud platform
Automation level	Semi-automatic (requires execution) /apply (Command triggered)	Fully automatic (continuous application in the background 24/7)	Manual (single-copy optimization assistance)
Customization capabilities	Extremely high (LaTeX source code-level customization, dual-proxy narrative reconstruction)	Medium (based on file autofill fields)	Medium to High (Modular Editing Suggestions)
Authenticity Guarantee	Dual Agent Verification(The review agent ensures zero fabrication)	Relying on the accuracy of user-preset files	Users are responsible for ensuring that AI provides optimization suggestions.
Technical threshold	high(Requires Python, Bun, and LaTeX environments)	Low(Pure webpage operation)	Low(Browser extension + webpage)

Application scenarios of AI Job Search

• Large-scale precision deliverySuitable for job seekers who need to apply for a large number of positions but refuse to use templates. It automatically generates LaTeX resumes and cover letters that are deeply customized for each company, improving application efficiency while maintaining high quality.
• Job seeking in a different industry/career changeSuitable for users who want to switch careers or enter emerging fields, the career path discovery function identifies transferable skills and reframes past experience into relevant qualifications for the new field.
• Complex background analysisSuitable for candidates with diverse professional experiences and a wide range of projects, this approach uses structured profiles to integrate scattered skills and achievements into a logically clear career narrative, avoiding disorganized application materials.
• Interview System PreparationFor scenarios requiring behavioral interviews, it automatically generates a STAR case library based on real-life experiences, providing a structured response framework and in-depth company research support.
• Seeking employment in professional fieldsSuitable for academic, research, and high-end technical positions where precise expression of professional skills is required, LaTeX generates professional documents that meet industry standards, ensuring the accuracy of technical terminology and project descriptions.