An AI-powered evaluation tool that uses dynamic expert routing to distinguish between genuine professional experience and mere methodology recitation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install interview-analysis
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install interview-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Interview Analysis Skill?
The Interview Analysis Skill is a sophisticated tool designed to move beyond surface-level interview summaries. By utilizing dynamic expert routing, it simulates the perspectives of world-class domain thinkers like Marty Cagan, Linus Torvalds, or Sheryl Sandberg to evaluate candidates. This approach allows hiring teams using Openclaw Skills to identify Battle Scars—genuine lessons learned from hard-won experience—rather than simple Methodology Recitation. It acts as a deep-decoding engine for professional capabilities across engineering, product, sales, and operations.
This skill doesn't just look at what the candidate said; it observes how they think and reconstructed their professional timeline to find inconsistencies. By integrating this into your workflow, you ensure that every hire meets a high bar of technical and cultural excellence while simultaneously improving your team's interviewing skills through meta-analysis of the interviewers themselves.
Interview Analysis Skill Use Cases
- Detecting red flags and timeline inconsistencies across multiple rounds of interviews for a single candidate.
- Distinguishing between candidates who memorize frameworks and those who apply first-principles thinking in high-stakes situations.
- Benchmarking candidate responses against the specific philosophies of industry leaders in their respective domains.
- Improving internal hiring standards by analyzing interviewer performance and bias through meta-analysis.
How Interview Analysis Skill Works
- The skill identifies the core competency domain of the role and automatically selects a combination of a Domain Expert and a Hiring Expert.
- It performs fact reconstruction by connecting experiences across interview rounds to check for logical gaps or exaggerated data.
- A deep decoding of STAR episodes is conducted to verify technical boundaries and solution biases.
- The AI performs a meta-analysis on the interviewers to evaluate depth, bias, and adherence to hiring standards.
- Standardized Markdown cards are generated and organized into a Zettelkasten-style structure for final decision closure.
Interview Analysis Skill Setup
To deploy this within your Openclaw Skills library, ensure your environment has access to the required templates folder.
# Navigate to your skill directory
cd skills/interview-analysis
# Ensure template files are present in /templates
ls templates/profile_template.md templates/insight_template.md
Once the templates are in place, you can trigger the analysis by providing interview transcripts and specifying the target role for expert routing.
Interview Analysis Skill Data Schema & Taxonomy
The skill organizes its output into a structured hierarchy within the people/{candidate_name}/analysis/ directory using the following schema:
| Document Type | Purpose | Metadata Included |
|---|---|---|
| Profile | Fact checking and competency portrait | Red flags, timeline gaps, core skills |
| Insight | Deep domain-specific analysis | AI capability, strategy depth, technical judgment |
| Meta-Analysis | Interviewer review | Probing depth, bias check, bar-raising evaluation |
| Structure Note | Hub document | Links to all cards for decision closure |
Interview Analysis Skill Advanced Features
- Dynamic Expert Routing: Automatically maps role types to specific thinkers like John Carmack for engineering or Don Norman for UX design.
- Zettelkasten Output: Generates interconnected Markdown cards that fit perfectly into personal or team knowledge management systems.
- Truth Extraction Engine: Specialized logic to identify when a candidate is deflecting blame or jumping to conclusions without validation.
- Custom Expert Injection: Flexibility to add non-mainstream experts to the routing logic to suit unique organizational needs through Openclaw Skills.
SKILL.md
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