mikonos

Interview Analysis

商业运营v1.0.0
作者:mikonos更新于 2026-05-11interview-analysis@clawhub_mikonos/interview-analysis
增长分析用户运营#Sales

据 AlphaMoat 统计,截至 2026-09,Interview Analysis 累计下载 4,008 次、获 2 个星标,在全部 5,078 个 AI 技能中排名第 2,555 位,在「商业运营」分类(297 个)中排名第 144 位。

累计安装
127
累计下载
4,008
星标
2
全站排名
#2,555
全站前 51% · 「商业运营」前 49%
平台累计安装累计下载星标评论
ClawHub ↗1273,9032-
SkillHub ↗1254,0082—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

该技能根据职位类型选择领域专家视角,对面试记录进行深入分析,关注候选人实际做过的事情和思考方式,以区分真实能力与方法论复述。面试记录和生成的候选人卡片可能包含机密招聘资料,应存放在有访问控制的位置,并明确保留和删除规则。 由人工复核依据,不要将分析直接作为最终录用决定。

资料发布于 2026-10-29

可以用来做什么

  • 分析面试记录中的实际项目经验
  • 根据职位类型组织评估视角
  • 从面试内容中提炼候选人洞察

什么时候用

  • 需要深入分析专业岗位面试记录时
  • 需要结合岗位特点组织评估维度时
  • 可以保护记录并在决策前复核证据时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

根据我提供的面试记录提炼候选人做过的具体工作及其推理过程;请逐条引用记录中的依据,不要将分析直接视为最终招聘决定。

月度数据趋势

累计下载4,008
2,1213,1354,1482026-03 · 累计下载 2,2612026-05 · 累计下载 3,1512026-06 · 累计下载 3,3172026-07 · 累计下载 3,5972026-08 · 累计下载 3,7702026-09 · 累计下载 4,00826-0326-09
星标2
1222026-03 · 星标 12026-05 · 星标 22026-06 · 星标 22026-07 · 星标 22026-08 · 星标 22026-09 · 星标 226-0326-09

2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。

月份累计下载环比星标
2026-094,008—2
2026-083,770+4.8%2
2026-073,597+8.4%2
2026-063,317+5.3%2
2026-053,151—2
2026-032,261—1

SKILL.md 原文

以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。

5.1 KB · ClawHub v1.0.0
---
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).
展开全部(共 82 行)
## 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 Type | Domain Expert (Methodology) | Hiring Expert (Validation) | Rationale |
|-----------|---------------------------|---------------------------|-----------|
| **Product Manager** | Marty Cagan / Julie Zhuo | Geoff Smart | Product Sense + Fact Check |
| **Software Engineer** | Linus Torvalds / John Carmack | Lou Adler | Engineering Judgment + Results Validation |
| **Growth Hacker** | Sean Ellis / Brian Balfour | Geoff Smart | Growth Methodology + Metrics Verification |
| **UX Designer** | Don Norman / Jony Ive | Lou Adler | UX Principles + Portfolio Validation |
| **Data Scientist** | Andrew Ng / DJ Patil | Geoff Smart | Technical Depth + Project Verification |
| **Operations** | Sheryl Sandberg / Reid Hoffman | Lou Adler | Scale Operations + Results Focus |
| **Sales/BD** | Aaron Ross / Jill Konrath | Geoff Smart | Sales 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."

「商业运营」分类下的热门技能

数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。