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interview（面试准备）

Agent Skill

interview 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。

总安装

14,666

周安装

630

GitHub Stars

公开资料未说明

下载量

5,141

OpenClaw

安装说明

本站只整理中文说明和来源信息，不托管安装包，也不代用户安装。

GitHub

来源数

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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：interview（面试准备）
来源仓库：https://github.com/agistack/interview
安装命令：
openclaw skills install interview
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 interview

简介

整合公司研究、故事构建与模拟面试练习的一体化准备系统。

适合求职面试、行为问答与技术测评场景。
输出包含个性化问题与反馈建议，需结合实际岗位调整。
不涉及真实面试安排，仅提供训练与模拟功能。
适用于 OpenClaw 环境，安装命令为 openclaw skills install interview。

SKILL.md

name: interview
description: Interview preparation system with company research, story building, and mock interview practice. Use when user mentions job interviews, interview prep, behavioral questions, salary negotiation, or follow-up messages. Researches companies, builds story libraries, runs mock interviews, prepares salary strategies, and drafts follow-ups. NEVER guarantees job offers.

Interview

Interview mastery system. Preparation that wins offers.

Critical Privacy & Safety

Data Storage (CRITICAL)

All interview data stored locally only: memory/interview/
No external job platforms connected
No application tracking systems integrated
No sharing of interview content
User controls all data retention and deletion

Safety Boundaries

✅ Research companies and roles
✅ Build story libraries from experience
✅ Run mock interviews with feedback
✅ Prepare salary negotiation strategies
❌ NEVER guarantee job offers
❌ NEVER provide false information
❌ NEVER replace genuine preparation

Data Structure

Interview data stored locally:

memory/interview/research.json - Company research briefs
memory/interview/stories.json - Story library
memory/interview/practice.json - Mock interview records
memory/interview/salary.json - Salary research and strategies
memory/interview/feedback.json - Post-interview notes

Core Workflows

Research Company

User: "Research Acme Corp for my interview Friday"
→ Use scripts/research_company.py --company "Acme Corp" --role "Product Manager"
→ Generate comprehensive research brief with talking points

Build Story

User: "Help me build a story about the project failure"
→ Use scripts/build_story.py --situation "project-failure" --lesson "learned"
→ Structure STAR format story with specific details

Mock Interview

User: "Run a mock interview for PM role"
→ Use scripts/mock_interview.py --role "Product Manager" --level senior
→ Ask realistic questions, provide honest feedback

Prepare Salary

User: "How should I handle the salary question?"
→ Use scripts/prep_salary.py --role "Product Manager" --location "SF"
→ Research market data, prepare negotiation strategy

Draft Follow-up

User: "Draft thank you email for today's interview"
→ Use scripts/draft_followup.py --interview "INT-123" --tone professional
→ Generate specific, memorable follow-up message

Module Reference

Company Research: See references/research.md
Story Building: See references/stories.md
Mock Interviews: See references/mock-interviews.md
Salary Negotiation: See references/salary.md
Difficult Questions: See references/difficult-questions.md
Follow-up Strategy: See references/followup.md
Handling Rejection: See references/rejection.md

Scripts Reference

Script	Purpose
`research_company.py`	Generate company research brief
`build_story.py`	Build STAR format stories
`mock_interview.py`	Run practice interview
`prep_salary.py`	Prepare salary strategy
`draft_followup.py`	Draft follow-up messages
`analyze_role.py`	Analyze job description
`identify_gaps.py`	Identify experience gaps
`log_feedback.py`	Log post-interview feedback

适合场景

OpenClaw 用户查找和安装 Skill 时

用户想查找某类 Agent Skill 时

需要根据任务场景推荐可安装能力包时

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明，方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

79.84%

按下载量换算4,105

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容，本身偏只读；真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/agistack/interview

SKILL.md 来源

clawhub.ai

/agistack/interview

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