Summary

Career-Ops provides an AI-powered job search pipeline, leveraging Claude Code to automate offer evaluation, CV generation, and application tracking. It targets job seekers aiming to optimize their search by focusing on high-fit opportunities, offering structured scoring and tailored application materials. The system aims to streamline the application process, ensuring users apply only to relevant roles and present their qualifications effectively.

How It Works

The system transforms Claude Code into a job search command center. It ingests job descriptions via URLs or text, classifying roles and performing a detailed A-F evaluation across 10 weighted dimensions, including CV match, compensation research, and interview preparation (STAR+R). This process generates tailored, ATS-optimized PDF CVs and populates a tracked pipeline. A key design principle is its self-customization: users can instruct Claude Code to modify modes, scoring weights, and scripts by editing the system's own configuration files.

Quick Start & Requirements

Installation involves cloning the repository, running npm install, and installing Playwright browser binaries (npx playwright install chromium). Users must then configure config/profile.yml and portals.yml, and create a cv.md file. Core functionality and customization are driven by interacting with Claude Code within the project directory. Full setup details are available in docs/SETUP.md.

Highlighted Details

• Comprehensive Evaluation: Includes role summary, CV match, level strategy, compensation research, personalization, and STAR+R interview story generation.
• ATS-Optimized PDFs: Generates tailored CVs with keyword injection, using specific fonts (Space Grotesk, DM Sans).
• Automated Portal Scanning: Features pre-configured scanning for over 45 companies and 19 job boards (e.g., Greenhouse, Ashby, Lever, Wellfound).
• Terminal Dashboard: A Go-based TUI provides visual browsing, filtering, and status management of the application pipeline.
• Batch Processing: Enables parallel evaluation of multiple job offers using sub-agents.

Maintenance & Community

The project is authored by Santiago, Head of Applied AI. No specific community channels (e.g., Discord, Slack) or explicit maintenance schedules are detailed in the README.

Licensing & Compatibility

The project is released under the MIT license, permitting broad use, including commercial applications and integration into closed-source projects.

Limitations & Caveats

Career-Ops is designed as a quality-focused tool, not for mass application, and requires user review before submission. Its effectiveness is tied to the capabilities of Claude Code, and initial setup requires familiarity with Node.js, Playwright, and AI agent interaction for customization.