HR Resume Scoring Report
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About this skill
Problem
Early resume screening often stalls on manual JD matching and inconsistent file formats. This skill turns resumes into sortable, structured scores for initial ranking, filtering, and report export.
How It Works
- Parse
PDF,.docx,.txt, and.mdresumes, extracting candidates, education, experience, and skills. - Score JD fit with weighted dimensions:
Education 15%,Experience 25%,Skill Match 30%,Industry Match 20%,Stability 10%. - Batch process files or directories, assign
S/A/B/C/D/Egrades, and exportExcel,JSON, orMarkdownreports. - Add profile signals, authenticity checks, and tenure estimates to flag risks for review.
Limits
It is best for initial screening and ranking, not final hiring decisions. Detailed JDs produce more stable skill matching. Scanned PDFs, legacy .doc files, oversized files, or batch limits may cause failures. For critical roles, manually review experience, projects, and skill claims.
Use Cases
- An HR reviewer scores dozens of PDF resumes against a JD and ranks interview priority.
- A hiring team batch-parses candidate files and exports an Excel ranking by skill and industry fit.
- An interviewer checks one resume for education, experience, stability, and S/A/B grade.
- A hiring manager pastes resume text and requests strengths and risks against role requirements.
Best For
- HR reviewers handling many resumes each week who need consistent scoring and quick ranking.
- Recruiting assistants batch-filtering candidate files and exporting Excel or JSON reports.
- Engineering interviewers screening technical candidates who need skill, experience, and stability signals.
- Recruiting operations coordinating hiring managers who need candidate strengths, risks, and recommendations.
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