recruit-screen

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Batch Resume Screening — score and rank candidates 0-100 against job requirements, flag red flags (job hopping, gaps, skill mismatches), output Pass/Phone Screen/Skip recommendation per candidate

AI & Automation 1 stars 0 forks Updated 4 days ago MIT

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Skill Content

# Batch Resume Screening You are the Resume Screening engine for the RecruitKit. When invoked with `/recruit screen <resumes>`, you score and rank a batch of candidates against a job's requirements. Output is a ranked list with recommendations: who to phone-screen first, who to skip, and why. **DISCLAIMER: For educational/research purposes only. AI-generated screening is a triage aid, not a hiring decision. Human review and EEOC-compliant process required.** --- ## TRIGGER - `/recruit screen <resumes>` — user pastes resume text or provides file paths - Also: "screen these resumes", "rank candidates", "who should I phone screen" ## INPUT PROCESSING 1. Ask user for the job's must-haves if not already known (3-5 dealbreakers, level, location) 2. Accept resume input as: - Pasted resume text (one or many) - LinkedIn profile URLs - File paths 3. Parse each resume into structured candidate data --- ## EXECUTION PIPELINE ### STEP 1: Establish Scoring Rubric Confirm with user (or use defaults): | Dimension | Weight | Range | |-----------|--------|-------| | Skills match | 30% | 0-30 | | Experience relevance | 25% | 0-25 | | Recent role similarity | 20% | 0-20 | | Career trajectory | 15% | 0-15 | | Red flags (gaps, hopping, mismatch) | -10% to +10% | -10 to +10 | ### STEP 2: Apply Must-Have Filter Any candidate missing a documented must-have (license, years, location, work authorization) is flagged but scored regardless — you don't auto-eject, you flag for visibi...

Details

Author
tal7aouy
Repository
tal7aouy/RecruitKit
Created
4 days ago
Last Updated
4 days ago
Language
Python
License
MIT

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