career-ops-hq

    career-ops-hq/career-ops

    #358 this week

    Open-source AI job search agent and job finder: scan job boards, score each job 1-5 against your CV before you apply, tailor an ATS-friendly resume and cover letter, get interview prep and a job application tracker. It helps you fill in each application; you press Submit. Runs locally in your AI coding CLI (Claude Code, Codex, OpenCode and more).

    ai-agents
    automation
    cli
    agent-skills
    ai-agent
    ai-job-search
    ats
    career
    JavaScript
    MIT
    75.3K stars
    14.0K forks
    75.3K GitHub watchers
    Updated Oct 17, 2026
    View on GitHub

    Build with Backblaze B2

    SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    Ranks #358 of 2,845 repositories GStars tracks this week (top 13%).

    5 releases in the last 90 days, the latest today, with 463 contributors on GitHub.

    The biggest single-day gain in the last year, +875 stars on Aug 18, coincided with release web-v0.7.0.

    Use Cases & Benefits

    • Provides an AI-powered local CLI tool to scan job portals, evaluate listings with a structured score, tailor CVs, and track job applications in a unified pipeline.
    • Enables personalized, data-driven job search management with AI reasoning beyond keyword matching, integrating evaluation, PDF generation, and application tracking locally.
    • Use for automating and optimizing job application workflows by evaluating multiple offers in parallel with tailored CVs and cover letters.
    • Use for job seekers wanting a privacy-focused, local-first system that keeps all personal data and AI interactions on their machine without cloud dependency.
    • Use for developers or AI enthusiasts who want to integrate job search capabilities into their AI coding CLI environment with customizable agent skills and modes.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    MIT

    Permissive: commercial use, modification and redistribution are allowed with attribution.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    I spent months applying to jobs the hard way. So I engineered the system I wish I had.

    Companies use AI to filter candidates. I just gave candidates AI to choose companies.

    Now it's open source.

    740+ job listings evaluated · 100+ personalized CVs · 1 dream role landed

    Also runs on any agent-skill-standard CLI

    Career-Ops (career-ops.org, also known as careerops) turns any AI coding CLI into a full job search command center. Instead of manually tracking applications in a spreadsheet, you get an AI-powered pipeline that:

    Important: This is NOT a spray-and-pray tool. Career-ops is a filter -- it helps you find the few offers worth your time out of hundreds. The system strongly recommends against applying to anything scoring below 4.0/5. Your time is valuable, and so is the recruiter's. Always review before submitting.

    Career-ops is agentic: whichever AI coding CLI you choose navigates career pages with Playwright, evaluates fit by reasoning about your CV vs the job description (not keyword matching), and adapts your resume per listing.

    Heads up: the first evaluations won't be great. The system doesn't know you yet. Feed it context -- your CV, your career story, your proof points, your preferences, what you're good at, what you want to avoid. The more you nurture it, the better it gets. Think of it as onboarding a new recruiter: the first week they need to learn about you, then they become invaluable.

    Excerpt from the career-ops-hq/career-ops README on GitHub (MIT license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Jul 21: +62Jul 24: +142Jul 25: +55Jul 26: +246Jul 27: +172Jul 28: +76Aug 7: +88Aug 12: +55Aug 15: +51Aug 18: +875Aug 19: +292Aug 20: +868Aug 27: +219Aug 28: +220Aug 29: +141Aug 30: +211Aug 31: +163Sep 1: +64

    +14,534 stars over 89 days across 28 snapshot days; best day +875 on Aug 18.

    Forks

    14.0K+2.1K

    Open issues

    347+105

    Compared with peers in AI Agents

    Fastest-growing repositories GStars tracks in this cohort for the week of Oct 11, by 7-day star growth

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    career-ops-hq/career-ops75.3K+045today
    Category median61.7K+5.3K75—

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