Resume Skill Extractor Plus (STAR Method)

Problem It Solves

Candidates often have enough experience but lack a repeatable way to turn projects, internships, self-study, and volunteer work into transferable resume skills. They list duties without context, task, action, or result, and cannot clearly see which gaps matter for a target role.

How It Works

• Initialization: asks for a target role and background, then organizes material into hard skills, soft skills, practical experience, and self-learning.
• STAR mining: probes each skill for Situation, Task, Action, Result, plus tools, methods, data, and impact; missing numbers can be filled with industry-average placeholders.
• Gap analysis: flags missing role-related skills, saves gap-analysis_[role].md, and recommends concrete courses, URLs, timelines, and outlines.

It generates resume_[role].md. Progress is saved in skill-list.md and asked-questions.md, supporting session resume; multiple role-specific resumes are kept separate.

Boundaries

It is best for drafting resume material, skill inventories, and role-specific resume versions. It does not replace manual JD verification or interview coaching. Placeholder industry averages must be replaced with verifiable numbers. The process depends on the user answering STAR follow-ups; when the target role is undefined, role matching is skipped and the flow switches to a generic completeness check.