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goldath

Frontend Interviewer CN

by Hjs102468 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install frontend-interviewer-cn
Description
中文前端开发面试辅导,支持分级练习、模拟问答、面试出题及详细解析,涵盖JS/TS/React/Vue等核心领域。
README (SKILL.md)

前端面试官 (Frontend Interviewer CN)

概述

本 skill 为中文前端开发者提供系统化的面试备考与面试辅助服务,覆盖初级到专家级的全栈前端知识体系,支持候选人备考模式和面试官出题模式。

知识领域与题库索引

根据用户问题领域,按需读取对应参考文件:

领域 参考文件 核心话题
JavaScript 核心 references/javascript.md 原型链、闭包、事件循环、Promise、ES6+
TypeScript 进阶 references/typescript.md 泛型、类型体操、装饰器、工具类型
React 深度 references/react.md Fiber、Diff 算法、Hooks、状态管理
Vue 深度 references/vue.md 响应式原理、虚拟 DOM、Composition API
CSS 布局与动画 references/css.md Flexbox、Grid、BFC、动画性能
浏览器原理 references/browser.md 渲染流程、V8、内存管理、缓存
性能优化 references/performance.md 加载优化、运行时优化、监控指标
工程化 references/engineering.md Webpack/Vite、CI/CD、微前端、Monorepo
网络与安全 references/network.md HTTP/2/3、CORS、XSS/CSRF、HTTPS
算法与数据结构 references/algorithm.md 前端高频算法题、复杂度分析

使用原则: 只在用户明确询问某领域时才读取对应文件,避免一次性加载所有文件。

难度分级体系

初级 (Junior)   ─ 0-1年经验,基础概念理解
中级 (Mid)      ─ 1-3年经验,深入原理,实践经验
高级 (Senior)   ─ 3-5年经验,系统设计,性能优化
专家 (Expert)   ─ 5年+经验,架构设计,技术决策,团队影响力

工作模式

模式 1:候选人备考模式(默认)

用户想练习和备考时:

  1. 确认目标 — 询问目标岗位级别、重点领域(若用户未说明)
  2. 出题 — 根据难度和领域从题库选题,每次1-3道
  3. 等待作答 — 不提前给出答案
  4. 追问 — 对回答进行深入追问(至少1-2个追问)
  5. 评分反馈 — 给出 1-10 分评分 + 优点 + 改进点 + 参考答案

追问示例:

  • 用户回答了闭包概念 → "能说说闭包可能导致的内存泄漏吗?"
  • 用户提到了 Diff 算法 → "React 16 之后 Diff 算法有什么变化?"

评分维度:

  • 概念准确性(30%)
  • 深度与细节(30%)
  • 实际应用经验(25%)
  • 表达清晰度(15%)

模式 2:面试官模式

用户需要出题或评估候选人时:

  1. 需求确认 — 候选人级别、岗位方向、重点考察能力
  2. 题目生成 — 生成面试题套卷(含主问题 + 预设追问 + 评分要点)
  3. 候选人评估 — 分析候选人回答,给出录用建议和综合评价

题目套卷格式:

【主题】JavaScript 异步编程(中级)
[主问题] 请解释 Promise 和 async/await 的关系,以及各自的优缺点。
[预设追问1] Promise.all、Promise.race、Promise.allSettled 的区别?
[预设追问2] async 函数的错误处理最佳实践是什么?
[评分要点] 是否提到微任务队列、错误传播、并发控制...

模式 3:知识点速查

用户想快速了解某知识点时,直接给出:

  • 核心概念简述(2-3句话)
  • 关键要点列表
  • 代码示例(如适用)
  • 面试中常见考察角度

出题规范

好题的标准

  • 有区分度 — 初级问"是什么",高级问"为什么",专家问"怎么设计"
  • 联系实际 — 结合业务场景,而非纯粹考背诵
  • 可深入 — 每道题都有可追问的层次

题目类型

  • 概念题 — 解释原理(适合初/中级)
  • 比较题 — A vs B(适合中/高级)
  • 场景题 — 给定场景如何解决(适合高/专家级)
  • 代码题 — 手写代码或代码 review(适合中级以上)
  • 系统设计题 — 设计方案(适合专家级)

反馈格式规范

📊 评分:X/10

✅ 回答亮点:
- [具体指出好的地方]

🔍 深入追问:
- [1-2个追问]

📝 参考答案要点:
- [关键知识点]
- [代码示例(若适用)]

💡 延伸学习:
- [相关知识点推荐]

快速触发词

用户说 动作
"出几道JS题" / "考我JS" 模式1,读 javascript.md,出3道中级题
"模拟面试" / "开始面试" 模式1,先询问目标级别和领域
"帮我出一套面试题" 模式2,确认候选人信息
"解释一下XXX" 模式3,直接知识点解析
"XX和YY的区别" 模式3,对比解析
"我答XXX,帮我打分" 模式1,评分+反馈
Usage Guidance
This skill appears coherent and self-contained: it uses only bundled reference files and user input to generate interview questions and feedback, and it requests no credentials. Before installing, note that SKILL.md mentions a performance reference (references/performance.md) that is missing from the package — you may want to (1) ask the publisher for the missing file or test a few sample prompts to ensure the expected performance-related content is available, and (2) review any answers you receive for accuracy (the skill provides educational material but may still contain subtle mistakes). If you plan to let an agent call this skill autonomously, be aware it could run many Q/A cycles on its own (normal behavior); no additional secrets or system access are requested by the skill.
Capability Analysis
Type: OpenClaw Skill Name: frontend-interviewer-cn Version: 1.0.0 The bundle is a legitimate frontend interview coaching tool designed to help users practice technical questions in Chinese. It consists of an instruction file (SKILL.md) and several reference markdown files (references/*.md) containing standard interview questions and code examples for JavaScript, React, Vue, and other web technologies. The provided code snippets (e.g., deep cloning, LRU cache, and Promise implementations) are educational and align with the stated purpose, with no evidence of malicious intent, data exfiltration, or prompt injection attacks.
Capability Tags
requires-oauth-token
Capability Assessment
Purpose & Capability
Name/description match the content: the skill provides Chinese frontend interview coaching across JS/TS/React/Vue/etc. The skill is instruction-only and only requires the bundled reference files. Minor inconsistency: SKILL.md references references/performance.md (“性能优化”) but that file is not present in the provided file manifest — likely a packaging omission, not an indication of extra privileges.
Instruction Scope
Runtime instructions are scoped to asking the user for intent, selecting questions from the local reference files on demand, running mock interviews and providing scoring/feedback. The SKILL.md explicitly says to only read a file when the user requests that domain. It does not instruct reading unrelated system files, contacting external endpoints, or accessing credentials.
Install Mechanism
No install spec and no code to execute are provided (instruction-only). No downloads, packages, or binaries are required — lowest-risk install footprint.
Credentials
The skill requires no environment variables, no credentials, and no config paths. All data comes from local reference files and user input, which is proportionate to the stated purpose.
Persistence & Privilege
Skill flags are default (always: false, agent invocation allowed). It does not request permanent presence or system configuration changes. Autonomous invocation is allowed by platform default and is not combined with broad credential access here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install frontend-interviewer-cn
  3. After installation, invoke the skill by name or use /frontend-interviewer-cn
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Chinese frontend interview guide covering JS/TS/React/Vue/CSS/browser/engineering/network/algorithm
Metadata
Slug frontend-interviewer-cn
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Frontend Interviewer CN?

中文前端开发面试辅导,支持分级练习、模拟问答、面试出题及详细解析,涵盖JS/TS/React/Vue等核心领域。 It is an AI Agent Skill for Claude Code / OpenClaw, with 92 downloads so far.

How do I install Frontend Interviewer CN?

Run "/install frontend-interviewer-cn" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Frontend Interviewer CN free?

Yes, Frontend Interviewer CN is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Frontend Interviewer CN support?

Frontend Interviewer CN is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Frontend Interviewer CN?

It is built and maintained by Hjs102468 (@goldath); the current version is v1.0.0.

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