Recruitment Assistant

Problem

Hiring workflows often get stuck between vague job descriptions, resume screening by intuition, and interview questions that are not tied to the candidate's actual gaps. The friction is not merely finding candidates, but making the JD, candidate background, and interview focus comparable. This skill structures that part of the process: define the role context, generate or import a JD, parse the resume, and produce a quantified fit assessment.

How It Works

It operates around a current position context. Key commands include:
- /new_position: create a role such as Java Backend, Internet, Senior.
- /jd or /set_jd: generate a job description or import an existing one; the imported JD is preferred for later evaluation.
- /resume: extract basics, work history, skills, projects, and certifications, then flag risks like high job-hopping frequency, career gaps, or skill mismatches.
- /match: score the candidate across skills, experience, education, stability, and growth potential, with 0-20 points per dimension and a total of 0-100, including concrete reasons for deductions.
- /interview: create tailored questions based on the role requirements and the candidate's profile, rather than generic prompts.

The emphasis is not replacing HR judgment, but making the decision trail clearer: whether the JD is role-specific, whether resume strengths and risks are identified, and whether the fit score can be traced back to concrete dimensions.

Boundaries

This skill is a text-assisted workflow. It does not contact candidates automatically, and it should not be treated as a system for publishing or storing resume data. Sensitive information should be redacted first. For niche roles, it is better to add industry context before evaluation. It is suitable for drafting recruiting materials, initial screening notes, and structured interview preparation, not for serving as a final hiring verdict.