๐ค Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round
Watch the demo video below:

๐ Whoโs it for
This workflow is designed for:
- Recruiters and Talent Acquisition Specialists who want to automate candidate interview prep.
- Hiring Managers conducting multiple interviews and needing personalized question sets.
- Technical Interviewers who want to save time and be well-prepared with relevant questions.
โ๏ธ How it works / What it does
The Smart Interview Assistant automates the interview preparation process in a few clicks:
- Accepts:
- Multiple resumes (PDFs)
- Selected job role
- Chosen interview round
- Extracts structured data from:
- The candidateโs CV
- The corresponding Job Description (JD)
- Uses GPT-4 to analyze:
- Candidate profile
- Role requirements
- Interview round context
- Generates:
- Tailored interview questions
- Expected answers
- A summarized interview prep report
- Sends the report directly to the hiring team via email (SMTP)
๐ Google Drive Structure
๐ Root Folder
โโโ ๐ jd/ # Stores all job descriptions in PDF format
โ โโโ Backend_Engineer.pdf
โ โโโ Azure_DevOps_Lead.pdf
โ โโโ ...
โโโ ๐ Positions (Google Sheet) # Maps Job Role โ JD File Link
๐ Sample Mapping Sheet:
Positions Sheet
Columns:
Job Role
Job Description File URL (pointing to PDF in jd/ folder)
๐ ๏ธ How to Set Up
Step 1: Configure API Integrations
- โ
Connect your OpenAI GPT-4 API Key
- โ
Enable Google Cloud APIs:
- Google Sheets API (to read job roles)
- Google Drive API (to access CV and JD files)
- โ
Set up SMTP credentials (for email delivery)
Step 2: Prepare Google Drive & Mapping Sheet
- Create a root folder on Google Drive
- Inside the root folder:
- Create a folder named
/jd/ and upload all job descriptions (PDFs)
- Create a Google Sheet named
Positions with the following format:
| Job Role | Job Description File URL |
|-----------------------------|--------------------------------------------|
| Azure DevOps Engineer | https://drive.google.com/xxx/jd1.pdf |
| Full-Stack Developer (.NET) | https://drive.google.com/xxx/jd2.pdf |
Step 3: Build the Application Form
Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects:
- ๐ Resume file (PDF)
- ๐งพ Job Role (dropdown)
- ๐ Interview Round (dropdown)
Step 4: Resume & JD Extraction
- ๐ Use
Extract from PDF to parse the resume content
- ๐ Retrieve the JD link from the
Positions sheet based on the selected Job Role
- ๐ Use
Download file to pull the PDF for processing
Step 5: Analyze with GPT-4
- Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output)
- Merge results
- Add manual input or mapping for the Interview Round metadata
Step 6: Generate Interview Report
- Use a second GPT-4 agent (e.g.,
HR Expert Agent) to:
- Generate 6โ8 tailored interview questions
- Include expected answers and rationale
Step 7: Deliver Final Report
- Format the content as:
- ๐ PDF (optional)
- ๐จ Email body
- Send the report to the recruiter, hiring manager, or interviewer via SMTP
โ
Requirements
- ๐ OpenAI GPT-4 API Key
- ๐ Google Drive (for resume and JD storage)
- ๐ Google Sheet (job role mapping)
- ๐ฌ SMTP credentials (host, username, password)
- ๐งฐ n8n self-hosted or cloud instance with:
- PDF Parser
- Google Sheets node
- HTTP Download node
- Email node
โ๏ธ How to Customize the Workflow
| Part |
Customization Options |
| Form UI |
Modify the design, dropdown options, or input validations |
| Job Description Source |
Replace Google Sheet with Notion, Airtable, or database |
| Interview Metadata |
Add job level, region, or language preference |
| AI Prompt Tuning |
Adjust prompt phrasing or temperature in GPT nodes |
| Report Format |
Generate PDF instead of email body using PDF node |
| Delivery Method |
Add internal HR portal webhook or generate downloadable link |