Career Ops
The Career Ops project is an open-source AI-powered job search system that integrates with AI coding command-line interfaces such as Claude Code, Codex, OpenCode, and Antigravity. It automates the process of scanning job portals, evaluating listings using a structured A-F rubric that produces a 1.0-5.0 score, tailoring CVs to specific job descriptions, and tracking applications over time. The system runs entirely locally, which helps keep personal data private and avoids reliance on third-party cloud services. Career Ops includes 14 distinct skill modes that let users customize the AI's behavior for different stages of the job search workflow. A Go-based dashboard provides a visual overview of tracked applications and evaluations, while PDF generation enables the creation of polished reports. Batch processing capabilities allow users to handle multiple job listings or applications simultaneously, making the tool suitable for both casual job seekers and those managing a high volume of opportunities. The project is structured as a set of skills that can be loaded into compatible AI coding environments, meaning it leverages the underlying language model's reasoning capabilities to interpret job descriptions and generate tailored application materials. Because it operates within local CLIs, users retain control over their data and can inspect or modify the underlying scripts to fit their specific needs. This approach contrasts with subscription-based SaaS job search platforms by offering full transparency and customization at no cost. Overall, Career Ops is positioned as a flexible, developer-friendly alternative for job seekers who are comfortable with command-line tools and want to automate repetitive parts of the job application process while maintaining control over their personal information.
- Category
- Open Source
- Pricing
- Open Source
Problem solved
Career Ops solves the tedious and repetitive aspects of job searching by automating job portal scanning, evaluating listings with a structured A-F rubric, tailoring CVs, and tracking applications. It reduces manual effort, provides consistent scoring, and keeps data local for privacy.
Use cases
- Automatically scan job portals for new listings
- Evaluate job listings with an A-F rubric and 1.0-5.0 score
- Tailor CV and cover letters to specific job descriptions
- Track job applications and their statuses
- Generate PDF reports of job search activity
- Batch process multiple job listings or applications
- Integrate with AI coding CLIs like Claude Code and Codex
Audience
- Developers
- Hobbyists
Pros
- Free and open-source with no subscription fees
- Runs locally, preserving privacy and data control
- Structured A-F scoring provides consistent job evaluation
- 14 skill modes for different job search tasks
- Batch processing and PDF export for efficiency
Cons
- Requires familiarity with AI coding CLIs
- Limited to environments like Claude Code or Codex
- May require manual setup and configuration
- Relies on external AI model APIs which may incur costs
- No dedicated graphical interface beyond the Go dashboard
Official website: https://github.com/santifer/career-ops
Canonical LambdaBase page: https://www.lambdabase.com/tools/career-ops