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career-ops-hq/career-ops

Open-source AI job search agent that scores job postings against your CV, drafts tailored resumes and cover letters, and tracks applications, running locally in your AI coding CLI.

Open-source alternative to:TealJobscan

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What is it?

career-ops is a job search agent that runs inside AI coding CLIs such as Claude Code, Codex and OpenCode. You paste a job URL or description, and it checks whether the posting is still open, scores the role from 1 to 5 against your CV, and recommends skipping weak fits. For roles worth pursuing, it drafts an ATS-friendly CV as PDF, a cover letter, and answers to application questions, plus interview preparation and company research.

The project also includes a portal scanner covering over 100 pre-configured companies and common ATS boards such as Ashby, Greenhouse, Lever and Wellfound, a pipeline tracker with deduplication and status management, rejection pattern analysis, and follow-up reminders. Data stays on your machine, and the system does not auto-submit applications or send email; you review each draft and submit yourself.

Setup is a single npx command, and the tool is configured through chat on first launch. It supports several AI CLIs and can be run with free or local models.

Key features

  • 01Scores each job 1-5 against your CV and flags weak fits before you apply.
  • 02Checks whether a posting is still live and whether it is a repost.
  • 03Generates ATS-readable PDF resumes and cover letters tailored to each job.
  • 04Scans 100+ pre-configured company career portals and common ATS boards.
  • 05Provides interview prep, STAR stories, salary negotiation scripts and application tracking.
  • 06Keeps all data local and never submits applications or sends email automatically.

Use cases

  • Deciding in seconds whether a specific job posting is worth applying to tonight.
  • Running a structured, high-volume job search while keeping every application tailored.
  • Preparing for interviews with company-specific research and practice sessions.
  • Tracking applications and analyzing which channels and patterns lead to responses.

Quick start

  1. 1

    Run the init command to set up career-ops

    npx @santifer/career-ops init

Things to know

  • It runs inside an AI coding CLI you already use, and your CV is sent to the AI provider you choose.
  • The README says the PDF fact check cannot judge every rewording, so you must read each CV before sending it.

Topics

#ai-agent#job-search#resume#cover-letter#career#ats#interview-prep#claude-code#cli#local-first

FAQ

What is career-ops?
Open-source AI job search agent that scores job postings against your CV, drafts tailored resumes and cover letters, and tracks applications, running locally in your AI coding CLI. career-ops is a job search agent that runs inside AI coding CLIs such as Claude Code, Codex and OpenCode. You paste a job URL or description, and it checks whether the posting is still open, scores the role from 1 to 5 against your CV, and recommends skipping weak fits. For roles worth pursuing, it drafts an ATS-friendly CV as PDF, a cover letter, and answers to application questions, plus interview preparation and company research.
Is career-ops free to use? What license does it have?
career-ops is open source under the MIT license. Check the license terms before using it in commercial products.
Is career-ops still maintained?
Actively maintained. The last commit to career-ops was on Oct 20, 2026.
What can I use career-ops for?
Deciding in seconds whether a specific job posting is worth applying to tonight. Running a structured, high-volume job search while keeping every application tailored. Preparing for interviews with company-specific research and practice sessions. Tracking applications and analyzing which channels and patterns lead to responses.
How do I install career-ops?
Run the init command to set up career-ops: npx @santifer/career-ops init
Where can I get career-ops?
The source code and installation instructions are on GitHub: https://github.com/career-ops-hq/career-ops

Summary generated by AI from the project's README. GitHub stats refresh daily.

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