Job Application Optimizer

Treats job applications like SEO campaigns, complete with keyword research, match scoring, and ATS optimization checklists. You feed it a job posting and your resume, it tells you whether to apply (skip if under 50% match), what tailoring level you need (light/medium/aggressive), and outputs keyword-optimized versions that actually parse through applicant tracking systems. The Resume SEO mental model is surprisingly useful: it maps keyword density, scan time, and content quality directly to resume components. Works with cv-creator for the actual document generation and tracks metrics like ATS pass rate and response rates. Honest about the tradeoffs too, like how aggressive tailoring risks over-optimization. If you're grinding through applications and wondering why nothing gets responses, this systematizes the optimization work most people do inconsistently.

skills.sh installs: 147
GitHub stars: 113
last updated: Jun 3, 2026

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Install

$ npx -y skills add erichowens/some_claude_skills --skill job-application-optimizer --agent claude-code

Installs into .claude/skills of the current project.

Files

Job Application Optimizer

Strategic job application planning and "Resume SEO" optimization. This skill teaches Claude to approach job applications like a marketing campaign - researching the market, qualifying opportunities, and optimizing content for maximum conversion.