interview-analysis
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
Dynamic Expert Routing for Candidate Assessment
Transform interview transcripts into deep capability insights. The AI automatically selects domain-specific evaluation frameworks (Marty Cagan for PM, John Carmack for Engineering) and distinguishes genuine Battle Scars from Methodology Recitation.
When to Use This Skill
Use this skill when:
- You have interview transcripts and need deep capability analysis
- You want to identify genuine "Battle Scars" vs "Methodology Recitation"
- You're evaluating candidates across diverse roles (PM, Engineering, Design, Sales, Data Science, etc.)
- You need structured output (Profile + Insights + Meta-Analysis cards) for hiring decisions
How It Works: Expert Routing
| Candidate Role | Domain Expert | Hiring Expert | Output Focus |
|---|---|---|---|
| Product Manager | Marty Cagan / Julie Zhuo | Geoff Smart | Product Sense + Fact Check |
| Software Engineer | Linus Torvalds / John Carmack | Lou Adler | Engineering Judgment + Results |
| UX Designer | Don Norman / Jony Ive | Lou Adler | UX Principles + Portfolio |
| Data Scientist | Andrew Ng / DJ Patil | Geoff Smart | Technical Depth + Projects |
| Growth / Sales | Sean Ellis / Aaron Ross | Geoff Smart | Methodology + Metrics Verification |
The AI selects the most appropriate expert combination based on role context. You can override or add experts; the table is reference, not constraint.
What You Get
| Output | Template | Purpose |
|---|---|---|
| Profile | templates/profile_template.md | Resume verification, red flags, competency |
| Insight | templates/insight_template.md | Domain-specific capability deep dive |
| Evaluation | templates/evaluation_template.md | Interviewer meta-analysis & recommendations |
| Structure Note | templates/structure_note_template.md | Hub document linking all analysis cards |
Cards are written to people/{candidate_name}/analysis/ in Zettelkasten-friendly Markdown.
Core Methodology
- Fact Reconstruction — Timeline verification, consistency across rounds, red-flag annotation (vague titles, exaggerated data).
- Deep Decoding — STAR episode analysis: first-principles vs SOP recitation, solution bias, technical boundary checks.
- Interviewer Meta-Analysis — Depth of probing, bias control, bar-holding.
Quick Reference
| Analysis Need | Template | Expert Framework |
|---|---|---|
| Candidate credibility | profile_template.md | Geoff Smart (Topgrading) |
| Role-specific capability | insight_template.md | Dynamic domain expert |
| Interview quality review | evaluation_template.md | Lou Adler + Kahneman |
Install
ClawHub (OpenClaw):
npx clawhub@latest install interview-analysis
Other (e.g. skills.sh):
npx skills add mikonos/interview-analysis
Compatible with Cursor, Claude Code, OpenClaw, and other agents that support the skills protocol.