Open-Source AI Job Search Tool 'Career-Ops' Launches Locally via AI Coding CLIs

An open-source project called career-ops has been released as a local AI job search agent and finder designed to operate directly within existing AI coding command-line interfaces. Created by developer Santiago Fernández de Valderrama Aparicio, the tool aims to help job seekers filter listings, score matches against personal CVs, and draft tailored application materials while keeping all user data locally on their machines.

According to project documentation, the utility is built around a human-in-the-loop design where the AI evaluates and drafts materials, but final submission actions remain strictly manual.

Core Functionality and Architecture

• Local Execution: User data—including CVs, tracking logs, and reports—remains entirely on the user's local machine, connecting directly only to user-chosen AI providers.
• CLI Compatibility: The tool integrates with various AI coding environments, including Claude Code, Codex, and Antigravity CLI, through an open Agent Skill Standard.
• Evaluation and Drafting: Scans job boards, checks if postings are active, scores fit, and generates ATS-friendly resumes and cover letters in PDF format.
• Manual Submission: The software explicitly avoids automated submissions, requiring users to review and manually execute final application steps.

Verification and Practical Considerations

The project relies on a modular system supporting over 55 job board feeds and configuration files (`portals.yml`) to scan targeted listings. Maintainers note that while the system incorporates checks to prevent the fabrication of metrics or facts in tailored CVs, users are advised to carefully review all generated documents before sending.

Interested users can review the codebase, documentation, and installation instructions directly on the project's official GitHub repository (`career-ops-hq/career-ops`).