PRODUCTIVITY
Automate Your Entire Job Search Pipeline with Local AI Agent Career-Ops
An open-source job-hunting copilot with 76k+ GitHub stars! Career-Ops runs locally in your terminal or coding assistant (Claude Code, Codex, OpenCode). It systematically scrapes and parses target job postings, objectively scores match compatibility from 1 to 5 against your master CV, generates tailored ATS-optimized resumes and cover letters in seconds, and synthesizes behavioral interview flashcards based on exact company pain points.
CORE TOOLS
Career-Ops (Open Source), LaTeX / Typst, Python 3.10+, Claude Code / Cursor / Codex
BEST FOR
Software engineers, product managers, data scientists, new graduates, career pivoters seeking optimal job placement
REQUIREMENTS
Local machine with Node.js 18+ or Python 3.10+, paired with a frontier reasoning model (Claude 3.5 Sonnet, DeepSeek-R1).
✦ WHY THIS WORKFLOW
Spraying generic resumes leads to swift rejection by automated Applicant Tracking Systems (ATS), while manual tailoring is exhausting. Career-Ops industrializes tailored job applications locally—maximizing interview callback rates without sacrificing data privacy.
✦
Interactive Workflow Animation Preview
Step-by-Step Action Checklist
0 / 4 Completed
READY-TO-USE PROMPT TEMPLATE
I am preparing a precision application for a Senior Staff AI Platform Architect position using open-source Career-Ops. Please provide: 1) [JD vs. Master CV Match Diagnostic Prompt]: An analysis prompt evaluating my master CV against the target JD across technical skills, architectural scale, and leadership, scoring compatibility from 1 to 5; 2) [ATS-Optimized STAR Bullet Point Rewriter]: Guidelines for transforming generic backend project descriptions into high-impact, metrics-driven bullet points formatted for automated ATS parsing; 3) [Mock Technical Architecture Interview Defense]: 3 challenging scenario questions on high-concurrency LLM inference scaling and failure recovery, accompanied by structured high-scoring talking points.