resume-targetlisted

# resume-target Target job position management -- parse JDs, calculate match scores, identify gaps for directed resume generation. ## JD Smart Parsing Extract structured data from job descriptions into the following fields: - **tech_required**: must-have technical skills (e.g. Java, Kubernetes, distributed systems) - **tech_preferred**: nice-to-have skills (e.g. Rust, GraphQL) - **responsibilities**: key responsibilities extracted from the JD - **requirements**: experience and education requirements - **keywords**: high-frequency terms for ATS keyword matching - **level**: estimated seniority level (P5 / P6 / P7 etc.) inferred from requirements and scope - **company**: company name Store all parsed fields in a single target JSON object. ## Match Score Calculation Score the user's profile against the parsed JD on a 0-100 scale with breakdown: | Dimension | Weight | Method | |----------------------|--------|-----------------------------------------------------| | Tech stack overlap | 40% | required skills (weighted 2x) + preferred (1x) | | Experience alignment | 30% | years of experience + domain match | | Keyword coverage | 30% | JD keywords found in profile and project descriptions| Additional outputs: - **match_gaps[]**: list of missing or weak areas (skills, experience, keywords) - Per-dimension sub-scores so the user can see where to improve - Overall score with a short