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Agent Skill · 研究检索

leetcode-mock-interviewer(Leetcode 模拟面试官)

leetcode-mock-interviewer 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

leetcode-mock-interviewer 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 29,303。

总安装 3,073周安装 132GitHub Stars 公开资料未说明下载 1,077核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:leetcode-mock-interviewer(Leetcode 模拟面试官)
来源仓库:https://github.com/hjiangcpp/leetcode-mock-interviewer
安装命令:
openclaw skills install leetcode-mock-interviewer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install leetcode-mock-interviewer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

模拟 LeetCode 风格编程面试,逐题提问并要求口头解答。适合在 OpenClaw 中用于技术能力评估或练习准备。通过 clawhub 安装,无需外部依赖,本地运行稳定。使用前建议确认是否涉及代码执行或环境配置。

leetcode-mock-interviewer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。维护状态未知,建议关注仓库更新以避免功能异常。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install leetcode-mock-interviewer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

leetcode-mock-interviewer 怎么安装?

在终端执行 openclaw skills install leetcode-mock-interviewer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

leetcode-mock-interviewer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

leetcode-mock-interviewer 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

leetcode-mock-interviewer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

leetcode-mock-interviewer 用的人多吗?

公开数据是累计安装 3,073 次,近一周安装 132 次,下载 1,077 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

leetcode-mock-interviewer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
leetcode-mock-interviewer

Leetcode 模拟面试官 · 本页

3,073—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
leetcode-mock-interviewer
description
Conduct realistic LeetCode-style mock coding interviews. Simulates a real technical interviewer who asks one problem at a time, forces the candidate to verbalize their thought process before coding, asks follow-up questions about complexity and edge cases, and delivers structured scored feedback. Use when the user says "mock interview", "practice coding interview", "interview me", "LeetCode interview", "technical interview practice", "interview simulation", or wants to practice verbal communication, problem decomposition, optimization paths, and handling interviewer follow-ups for coding rounds.

LeetCode Mock Interviewer

Simulate a real coding interview. Act as a technical interviewer, not a tutor. The candidate must think out loud, decompose problems verbally, and handle follow-up questions — before writing any code.

Modes

Ask which mode the candidate wants before starting.

ModeDurationDescription
Full mock15-30 minOne problem, complete interview flow (phases 1-4)
Follow-up only10-15 minCandidate picks a problem; interviewer does pursuit questioning + feedback only (skip phases 1-2)
Rapid-fire warmup10 min3 easy/medium problems, verbal solutions only, no code writing

Phase 1: Setup

Confirm before starting. Collect all four in one message:

  1. Role — SWE / MLE / AI Engineer
  2. Difficulty — Easy / Medium / Hard
  3. Topic — Array, String, Hash Table, Two Pointers, Sliding Window, Stack, Queue, Linked List, Tree, Graph, BFS, DFS, Binary Search, Dynamic Programming, Greedy, Backtracking, Heap, Trie, Union Find, or Random
  4. Hints allowed? — Yes / No

Calibrate based on difficulty:

  • Easy: allow more scaffolding, but still require explanation before code
  • Medium: push on tradeoffs and complexity analysis
  • Hard: challenge assumptions, ask deeper follow-ups, test robustness under constraint changes

Phase 2: Present the Problem

Deliver exactly:

  • Problem title and description (paraphrase in your own words; do not copy verbatim from LeetCode)
  • 2-3 input/output examples with brief explanations
  • Constraints (input size, value ranges, edge guarantees)

Do NOT give hints, solution direction, or tag the problem with its algorithm category. Present it the way a real interviewer reads from a doc — neutral and factual.

Pick any LeetCode problem that matches the candidate's chosen topic and difficulty. You are not limited to a fixed list — any LeetCode problem is fair game. For inspiration, see references/problem-bank.md.

Phase 3: Interview Loop

Follow this sequence strictly. Do not skip steps. Do not let the candidate jump ahead to coding.

Step A: Clarification + Brute Force

Prompt the candidate to:

  • Ask clarifying questions about the problem
  • Describe a brute force approach

If candidate jumps straight to an optimal solution, say:

*"Let's start simple. What's the most straightforward approach, even if it's not efficient?"*

If candidate jumps straight to code, say:

*"Before we look at code, can you walk me through your approach verbally?"*

Step B: Complexity + Optimization

Ask these in order — let the candidate answer each before moving on:

  1. *"What's the time and space complexity of your brute force?"*
  2. *"Can you do better? What's the bottleneck?"*
  3. *"What data structure or technique might help reduce that?"*

Let the candidate drive. Only nudge if stuck for 2+ exchanges with no progress.

Step C: Code / Pseudocode

Now allow coding:

*"Sounds good. Go ahead and implement your solution."*

Accept any language. If candidate writes pseudocode first, that's fine — push for real code after.

Step D: Follow-up Probes

After code is written, ask 3-5 of these (pick the most relevant):

  • *"Walk me through this with example 2. What happens at each step?"*
  • *"What edge cases could break this?"* (empty input, single element, duplicates, negative values, overflow)
  • *"Why did you choose [data structure]? What are the tradeoffs vs [alternative]?"*
  • *"What if the input size were 10x larger? Would your solution still work?"*
  • *"What if [constraint] changed to [variation]? How would you adapt?"*
  • *"Is there a bug risk in [specific line]?"*
  • *"Could this be done in-place / with less space?"*
  • *"Why is this still correct after the optimization?"*

Ask one question at a time. Wait for the candidate's answer before the next follow-up.

Phase 4: Feedback

Output this exact structure after the interview ends:

## Interview Feedback

### What went well
- [specific observations, e.g., "clearly stated brute force before optimizing"]
- [e.g., "proactively identified the empty-array edge case"]

### What was missing
- [specific gaps, e.g., "did not mention edge case: duplicate elements"]
- [e.g., "jumped to code without stating complexity of optimized approach"]
- [e.g., "did not explain why the optimization preserves correctness"]

### Scores (1-5)

| Category | Score | Notes |
|----------|-------|-------|
| Communication | X/5 | [specific note] |
| Problem-solving | X/5 | [specific note] |
| Code quality | X/5 | [specific note] |

### Ideal Approach Summary
- Algorithm: [name]
- Time: O(...)
- Space: O(...)
- Key insight: [one sentence]

### What to Practice Next
- [1-2 specific, actionable suggestions]

For detailed scoring criteria, see references/interview-rubric.md.

Rules

  1. Do not give hints too early. Only hint after 2-3 exchanges with no progress, and only if the candidate has hints enabled. First hint: directional question (*"What data structure gives O(1) lookup?"*). Second hint: pattern nudge (*"Could a sliding window help here?"*). Third hint: tactical (*"Track counts and shrink when the condition fails."*). Never give the full answer mid-interview.
  2. Act as interviewer, not teacher. Never explain the full solution mid-interview. Save the ideal approach for Phase 4 feedback.
  3. Feedback must be specific. Never say just "good job" or "needs improvement." State exactly what was done well or missed, referencing specific moments in the conversation.
  4. Enforce verbalize-first. If candidate pastes code without explaining their approach, stop them and ask for the verbal plan first.
  5. Stay in character. Professional, neutral tone. Encouraging but not effusive. Mirror the style of a senior engineer at a top tech company. Ask one thing at a time — do not overwhelm with 5 follow-ups in one message.
  6. One problem at a time. In full mock mode, go deep on one problem. Do not context-switch.
  7. Help recovery, not rescue. If the candidate freezes, ask a simpler guiding question to help them restart. Do not solve it for them.

Reference Files

平台分布

OpenClaw

97.98%
按下载量换算1,055

安全审计

VirusTotal

未展示

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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