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interview-analysis访谈分析

Agent Skill

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。

总安装

83,866

周安装

3,360

GitHub Stars

2

下载量

27,149
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

2

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-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

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openclaw skills install interview-analysis

简介

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。

SKILL.md

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."

适合场景

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02

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03

需要根据任务场景推荐可安装能力包时

04

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能力 3

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能力 4

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能力 5

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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

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按下载量换算25,034

安全审计

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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

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