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Install in OpenClaw
/install interview-assistant
Description
结构化面试助手 - 基于 JD 和简历生成 STAR 面试题库
README (SKILL.md)
结构化面试助手技能
技能概述
结构化面试助手是一个专业的 HR 工具，融合行为面试法和 STAR 原则，支持 JD+简历对比分析，生成针对性的面试问题。
触发条件
当用户需要：
- 根据岗位描述生成面试题库
- 结合候选人简历生成针对性问题
- 准备结构化面试流程
- 获取面试评分维度和标准
功能特性
- ✅ JD 解析 - 提取岗位核心能力要求
- ✅ 简历解析 - 提取候选人经历亮点
- ✅ 差距分析 - JD 要求 vs 简历匹配度
- ✅ STAR 问题生成 - 基于行为面试法
- ✅ 评分卡 - 5 分制 STAR 评分标准
- ✅ 简洁输出 - 核心信息一目了然
使用方法
方式 1：只有 JD（生成通用面试题库）
interview-assistant --jd "招聘高级产品经理，负责 B 端 SaaS 产品，5 年以上经验" --questions 5
方式 2：JD + 简历（生成针对性问题）
interview-assistant --jd "招聘高级前端工程师，5 年以上经验，精通 React/Vue" --resume "张三，8 年前端经验，本科，曾在腾讯负责 React 项目" --questions 3
参数说明
--jd/-j: 必需参数，岗位描述--resume/-r: 可选参数，候选人简历内容--questions/-q: 生成问题数量（默认 5 个）--output/-o: 输出格式（markdown/json/text）
输出内容
- 岗位信息 + 候选人信息 + 匹配度
- 能力匹配分析表（✅/⚠️/❌ 标记优先级）
- STAR 原则面试问题（S/T/A/R 引导 + 评分标准）
- 分析总结
STAR 原则
- Situation（情境）：当时的背景是什么？
- Task（任务）：你面临的任务/目标是什么？
- Action（行动）：你具体做了什么？
- Result（结果）：最终结果如何？有什么收获？
技术实现
- 基于 Node.js 的 CLI 应用
- JD 解析模块提取业务领域和专业技能
- 简历解析模块提取候选人经历
- 差距分析模块计算匹配度
- STAR 问题生成模块生成场景化问题
Usage Guidance
This skill appears coherent and low-risk, but it requires you to have or install a separate Node.js CLI named 'interview-assistant'. Before installing or globally linking any package: 1) verify the source of that CLI (npm package name or repository) and inspect its package.json and code if possible; 2) prefer installing from an official or trusted repository rather than running unknown npm link commands; 3) note run.sh references a local path (/Users/claw/...), which is just an installation hint and can be ignored or adapted to your environment. If you plan to install a third-party 'interview-assistant' package, review that package for network calls or unexpected file access prior to global linking.
Capability Assessment
Purpose & Capability
Name/description (JD+resume → STAR interview questions) match the declared requirement for an 'interview-assistant' CLI and the SKILL.md examples. Requiring a CLI binary is proportionate for a CLI-based skill.
Instruction Scope
SKILL.md and run.sh only describe running the interview-assistant CLI with JD/resume inputs and formatting options. There are no instructions to read unrelated files, export credentials, contact unknown endpoints, or gather system state beyond checking the CLI is installed.
Install Mechanism
No install spec is provided (instruction-only). run.sh expects a globally available CLI and suggests 'npm link' for local installation; no downloads or extract steps are present.
Credentials
No environment variables, credentials, or config paths are required. The skill's functionality does not appear to need secrets or broad system access.
Persistence & Privilege
Skill is not always-on, does not request elevated persistence, and does not modify other skills or global agent configuration.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install interview-assistant - After installation, invoke the skill by name or use
/interview-assistant - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
interview-assistant 1.0.0 初始发布
- 支持输入 JD（岗位描述）自动生成结构化 STAR 面试问题
- 支持同时输入 JD 和简历，生成针对性行为面试题与匹配分析
- 自动提取岗位与候选人的核心能力要求和优势点
- 提供 5 分制 STAR 评分卡与能力匹配分析表
- 输出支持多种格式（markdown/json/text）
Metadata
Frequently Asked Questions
What is Interview Assistant?
结构化面试助手 - 基于 JD 和简历生成 STAR 面试题库. It is an AI Agent Skill for Claude Code / OpenClaw, with 455 downloads so far.
How do I install Interview Assistant?
Run "/install interview-assistant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Interview Assistant free?
Yes, Interview Assistant is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Interview Assistant support?
Interview Assistant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Interview Assistant?
It is built and maintained by wanwan2qq (@wanwan2qq); the current version is v1.0.0.
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