Add Resume Radar skill#1205
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What problem it solves
Modern resume screeners (like HackerRank's open-source
interviewstreet/hiring-agent) are not keyword ATS filters. They read the resume PDF, pull the candidate's live GitHub via API, classify every repo as open-source vs personal, and score four weighted categories plus bonuses and deductions.Beating Resume Screeners teaches Claude to see what that agent sees and fix the highest-leverage gaps, using real signals and honest framing only (it never fabricates experience, PRs, or metrics).
Who uses this workflow
Software engineers and new grads applying for jobs whose resumes are auto-screened before a human sees them.
What's included (more than a single SKILL.md)
SKILL.mdfollowing the Agent Skills spec (audit / simulate / optimize workflow)references/RUBRIC.mddocumenting the full reverse-engineered 120-point rubricscripts/github_enrich.py(Python stdlib only, no deps) that reproduces the agent's live GitHub repo classification, which is what caps the open_source scorescripts/test_github_enrich.pyoffline unit testsevaluations.jsonbehavioral evalsExample usage
Claude runs the enrichment script, detects (for example) that all repos are single-contributor
self_projecttype, explains the open_source category is capped at ~10/35, and gives a concrete honest action to close the gap.Repo: https://github.com/SakethKanchi/beating-resume-screeners (MIT). Tested with Claude Code. Not affiliated with HackerRank.