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Career-Ops turns Claude Code into an AI job search pipeline. 12 modes, A-F scoring across 10 dimensions, ATS-optimized CVs per listing, batch processing of 122 URLs in parallel. 631 evaluations, 68 apps sent. Open source, 9.1K GitHub stars.
Career-Ops provides a terminal UI dashboard to browse, filter, and sort the application pipeline. It maintains integrity through automated merge, dedup, status normalization, and health checks, eliminating spreadsheet chaos and ensuring no opportunities are lost or duplicated.
Career-Ops automatically generates keyword-injected PDFs customized per job description using Space Grotesk and DM Sans design. The system reads the job description and user's CV, then adapts the resume to highlight relevant skills and experience, increasing interview callback likelihood.
Career-Ops provides an A-F scoring system across 10 weighted dimensions (role summary, CV match, level strategy, compensation research, personalization, interview prep) to help users filter and rank job offers objectively rather than applying broadly. Users feed the system their CV and preferences, and it learns to recommend only high-fit roles (4.0+/5.0 score).
Career-Ops accumulates STAR+Reflection stories across evaluations, building a story bank of 5-10 master narratives that answer any behavioral question. Users can reference these during interview prep and negotiation, backed by the system's deep analysis of their background and the role requirements.
Career-Ops includes a portal scanner pre-configured for 45+ companies (Anthropic, OpenAI, ElevenLabs, Retool, n8n, etc.) and supports custom queries across Ashby, Greenhouse, Lever, and Wellfound. Users can scan multiple job boards in parallel to build a centralized pipeline without manual browsing.