[GitHub Trending] santifer/career-ops

6.3 relevance

AI job search tool, interesting but not directly relevant to the reader's professional focus areas.

AI/ML github.com

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Why It Matters

For a solutions architect evaluating AI/ML agent orchestration patterns, career-ops demonstrates a practical multi-agent pipeline (sub-agents for parallel evaluation, Playwright for browser automation, CLI integration with any agent framework) applied to a real-world hiring workflow, offering a reference architecture for building agentic tools that combine structured scoring, PDF generation, and external API scanning.

Key Takeaways

Adopt career-ops as a case study for agentic CLI design: separate legitimacy checks from scoring, use Playwright for dynamic page interaction, and require explicit user context to bootstrap agent quality.

Open-source AI job search: scan job portals, evaluate listings with a structured A-F rubric into a 1.0-5.0 score, tailor your CV, track applications — runs locally in your AI coding CLI (Claude Cod...

Summary

Career-ops is an open-source CLI tool that transforms any AI coding agent into a job search command center, enabling batch evaluation of offers, ATS-optimized CV generation, and automated portal scanning across Greenhouse, Ashby, Lever, and Wellfound. Built by a practitioner who evaluated 740+ listings and landed a Head of Applied AI role, it uses Playwright for agentic navigation and a weighted A-F scoring system with a separate Block G for scam/ghost-job detection. The tool explicitly discourages spray-and-pray applications, recommending a 4.0/5 minimum threshold, and requires upfront context feeding to improve evaluation quality over time.

Author

santifer