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Agent Skill · 效率

interview-analysis(访谈分析)

interview-analysis 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

interview-analysis 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 512。

总安装 83,866周安装 3,360GitHub Stars 2下载 27,149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:interview-analysis(访谈分析)
来源仓库:https://github.com/mikonos/interview-analysis
安装命令:
openclaw skills install interview-analysis
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-analysis

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

使用动态专家路由进行深度访谈分析。根据角色类型自动选择顶级领域思想家,以区分真正的能力和绩效,通过方法论背诵识别战斗伤痕。适用于任何专业职位,包括产品管理、工程、设计、运营、销售和数据科学。

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 interview-analysis;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

interview-analysis 怎么安装?

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

interview-analysis 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。

interview-analysis 需要什么权限?

权限级别是只读。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。

interview-analysis 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。

interview-analysis 用的人多吗?

公开数据是累计安装 83,866 次,近一周安装 3,360 次,下载 27,149 次,GitHub 2 星。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。

interview-analysis 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
interview-analysis

访谈分析 · 本页

83,8662只读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
interview-analysis
description
Deep interview analysis using dynamic expert routing. Automatically selects top domain thinkers based on role type to distinguish genuine capability from performance, identifying Battle Scars over Methodology Recitation. Applicable to any professional position including product management, engineering, design, operations, sales, and data science.

Interview Analysis Skill

Core Mission: Transform interview transcripts into deep insights. Core Logic: Don't listen to what candidates "say" (Methodology Recitation), observe what they've "done" (Battle Scars) and "how they think" (First Principles).

1. Dynamic Expert Activation (Expert Routing)

Core Principle

Based on role type and evaluation dimensions, automatically select the best minds combination for that domain:

Three-Step Expert Selection:

  1. Identify core competency domain: Product/Engineering/Operations/Design/Sales/Data Science/...
  2. Match top domain thinkers: Recognized methodology masters or practitioners in the field
  3. Combine hiring experts: Geoff Smart (fact-checking) + Lou Adler (competency validation)

Common Role-Expert Mapping (Non-Exhaustive)

Role TypeDomain Expert (Methodology)Hiring Expert (Validation)Rationale
Product ManagerMarty Cagan / Julie ZhuoGeoff SmartProduct Sense + Fact Check
Software EngineerLinus Torvalds / John CarmackLou AdlerEngineering Judgment + Results Validation
Growth HackerSean Ellis / Brian BalfourGeoff SmartGrowth Methodology + Metrics Verification
UX DesignerDon Norman / Jony IveLou AdlerUX Principles + Portfolio Validation
Data ScientistAndrew Ng / DJ PatilGeoff SmartTechnical Depth + Project Verification
OperationsSheryl Sandberg / Reid HoffmanLou AdlerScale Operations + Results Focus
Sales/BDAaron Ross / Jill KonrathGeoff SmartSales Methodology + Performance Verification
[!IMPORTANT] Flexibility Principle: The table above is for reference only. Flexibly select the most appropriate expert combination based on specific role and candidate background. Encourage Innovation: If you believe a non-mainstream expert is better suited to evaluate this candidate, make that choice and explain your rationale. Core Question: "Who can best identify imposters in this role? Whose framework best validates core competencies?"

2. Execution Workflow

Step 1: Fact Reconstruction & Red Flag Scan

  • Timeline Reconstruction: Connect experiences scattered across multiple interview rounds, checking for logical gaps.
  • Consistency Verification: Compare different versions of the same story told to different interviewers (e.g., reasons for leaving, project failures).
  • Red Flag Annotation: Mark all vague titles (e.g., SPM), exaggerated data, and attribution fallacies ("it was all market/technology's fault").

Step 2: Deep Decoding - STAR Episodes

  • Tactic: Select 1-2 core cases (e.g., startup project, most challenging project) for microscopic analysis.
  • Truth Extraction:

* Methodology Check: Is the candidate reciting SOPs (MECE, SWOT) or applying first principles? * Solution Bias Check: Did they jump straight to "add features," or first conduct "value validation"? * Technical Boundary Check: For technical challenges, did they "deflect blame" or "anticipate"?

Step 3: Interviewer Meta-Analysis

  • Subject: Evaluate interviewer (you/colleagues) performance.
  • Dimensions:

* Depth: Did they probe at critical moments? Or let it pass? * Bias: Did they draw conclusions too early or ask leading questions? * Bar: Did they maintain A Player standards?

Step 4: Card-based Output (Zettelkasten Output)

Generate Markdown cards using the following standard templates, saved to people/{candidate_name}/analysis/. Be sure to read template content before filling in analysis results.

  • Profile (Comprehensive Portrait):

* Template path: templates/profile_template.md * Purpose: Fact checking, red flag scanning, core competency assessment.

  • Insight (Deep Analysis):

* Template path: templates/insight_template.md * Purpose: Deep dive into specific domains (e.g., AI Capability, Product Strategy).

  • Meta-Analysis (Interviewer Review):

* Template path: templates/evaluation_template.md * Purpose: Evaluate interviewer performance and organizational recommendations.

  • Structure Note (Hub Document):

* Template path: templates/structure_note_template.md * Purpose: Serves as hub connecting all analysis cards above, forming decision closure.

3. Usage Examples

  • "Analyze Li Yashuang's three interview rounds, focusing on AI capabilities."
  • "Review this interview to see where we interviewers did well and where we missed opportunities."
  • "Use Marty Cagan's perspective to analyze this candidate's product thinking."

平台分布

OpenClaw

92.21%
按下载量换算25,034

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

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。目前只有一个公开来源,建议同时核对源仓库。

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