AI Agent Hub
Back to skills
🏢

Interview Hiring Efficiency Workspace

Business Operations Updated 2026.08.30

Paste the following prompt into your AI chat to install this skill:

Follow https://skillhub.cn/install/skillhub.md to install @kunlungrowth/kunlun-interview.

About this skill

Problem

Hiring processes often break down at concrete points: a job description reads like marketing copy instead of a filter; resume screening relies on brand-name companies and tenure heuristics; interviewers improvise questions, so candidates are probed at inconsistent depth; evaluation lacks anchors and comparison becomes impression-based; salary conversations lack budget clarity, market range, and risk checks, causing offers to stall.

How It Works

kunlun-interview organizes recruiting work into six triggerable capabilities: JD writing, resume screening, interview question banks, interview evaluation, salary negotiation, and structured interview SOP. Given inputs such as role, level, team, budget, or candidate behavior, it produces structured artifacts: responsibilities/requirements/bonus items, scoring tables, rejection reasons, behavior/professional/scenario questions, 1–5 behavioral anchors, and salary range with negotiation language.

The workflow emphasizes evidence: resume screening separates hard requirements from soft signals, scores against thresholds, and records specific rejection reasons. Structured interviews move through opening, STAR probing, technical validation, candidate questions, and immediate scoring. Evaluation avoids halo effects by tying each dimension to observable behavior.

Boundaries

The skill provides methods, templates, and checklists; it does not replace qualification judgments or connect to external accounts, paid services, or APIs. Output quality depends on input specificity: the clearer the role, level, budget, and market context, the more actionable the result. Compliance should be maintained by evaluating only job-relevant factors and excluding unrelated attributes such as age, gender, marital status, or region.

Use Cases

  • Draft a mid-level backend JD with responsibilities, requirements, bonus items, and team support for posting.
  • Score 20 resumes against hard requirements and project relevance, then mark recommend, pending, and drop with reasons.
  • Prepare behavior, technical, and scenario questions by role level, plus 1-5 scoring anchors for each dimension.
  • Prepare a salary range from market data, budget cap, and candidate expectation, with negotiation language and risks.

Best For

  • HRBP coordinating multiple roles and needing consistent JD, screening, and evaluation standards.
  • Recruiter triaging many resumes into recommend, pending, and reject with reviewable reasons.
  • Hiring manager preparing behavior questions, technical prompts, and scoring anchors before interviews.
  • Startup founder running small-team hiring from JD drafting to offer decision with structured references.