A specialized tool for generating structured Feishu interview documents from resumes and providing comprehensive assessments from transcripts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install interview-question-gen
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-question-gen 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 Question Generator & Evaluator?
This Openclaw Skills solution is designed to automate the end-to-end recruitment workflow for activity operations roles. It bridges the gap between receiving a candidate's resume and finalizing their evaluation by leveraging AI to analyze candidate backgrounds, cross-reference them with product frameworks, and generate structured interview guides. By using this Openclaw Skills integration, hiring managers can ensure consistent questioning and high-quality documentation within their Feishu workspace.
The skill operates in two distinct phases: initial preparation and post-interview evaluation. It utilizes vision-based analysis for PDF resumes and integrates directly with Feishu APIs to create and update documents, ensuring that every interview is data-driven and properly recorded for the hiring team.
Interview Question Generator & Evaluator Use Cases
- Preparing customized interview question sets based on specific candidate work history and education.
- Generating localized Japanese language assessment questions for international roles.
- Creating structured evaluation reports by analyzing interview transcripts or recordings.
- Maintaining a centralized and organized repository of interview documents in Feishu for team collaboration.
How Interview Question Generator & Evaluator Works
- The agent processes the candidate's resume by converting PDF pages into images for high-accuracy visual data extraction.
- It retrieves the latest product context from a designated Feishu wiki to align questions with the current product roadmap.
- A structured markdown file is generated, featuring tailored sections ranging from ice-breakers to role-specific scenario planning.
- The Openclaw Skills agent uses a Node.js helper script to create a official document in a specific Feishu folder, adding necessary collaborators.
- Post-interview, the agent reads the transcript and appends a detailed performance evaluation, including star ratings and risk assessments, to the existing document.
Interview Question Generator & Evaluator Setup
To deploy this skill within your workspace, ensure you have the necessary environment for Python and Node.js.
- Install the required Python library for resume processing:
pip install PyMuPDF
Configure your Feishu Bot credentials and ensure the
feishu_bot_doc.mjsscript is in your project directory.Verify access to the target Feishu folder ID:
AZ3nfFtial4bHTdOFahcdcfxnub.
Interview Question Generator & Evaluator Data Schema & Taxonomy
The skill manages information through a combination of temporary local storage and cloud-based document structures:
| Data Component | Format | Description |
|---|---|---|
| Resume Buffer | Image (PNG) | Extracted pages stored at /tmp/resume_p{n}.png |
| Interview Guide | Feishu Doc | Structured into 7 sections including Japanese oral exams |
| Assessment Rubric | Markdown | Appended data with 1-5 star ratings across 6 dimensions |
| Product Context | URL/Wiki | Reference data sourced from internal Feishu knowledge bases |
Interview Question Generator & Evaluator Advanced Features
- Vision-based resume analysis using PyMuPDF for reliable data extraction from complex PDF layouts.
- Dynamic localization that generates oral exam questions entirely in Japanese without mixing languages.
- Automated collaboration management by instantly assigning document permissions to relevant hiring stakeholders.
- Context-aware scoring rubrics that adapt based on the specific employer and projects mentioned in the candidate's history.
SKILL.md
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