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Generate tailored interview questions with GPT-4 based on CV, JD, and round

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Generate tailored interview questions with GPT-4 based on CV, JD, and round preview
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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round Watch the demo video below: [![Watch the video](https://s3.ap southeast 1.amazonaws.com/automatewith.me/smart interview p...

Best for

  • HR automation workflows
  • Multimodal AI automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, n8n-nodes-base.formtrigger, n8n-nodes-base.extractfromfile, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.googlesheets, n8n-nodes-base.googledrive, @n8n/n8n-nodes-langchain.agent

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Trung Tran.

Original n8n.io source

1.1 Workflow description

Title
Generate tailored interview questions with GPT-4 based on CV, JD, and round
Workflow name
Generate tailored interview questions with GPT-4 based on CV, JD, and round

πŸ€– Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round

Watch the demo video below:

πŸ“Œ Who’s 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.

βš™οΈ How it works / What it does

The Smart Interview Assistant automates the interview preparation process in a few clicks:

  1. Accepts:
    • Multiple resumes (PDFs)
    • Selected job role
    • Chosen interview round
  2. Extracts structured data from:
    • The candidate’s CV
    • The corresponding Job Description (JD)
  3. Uses GPT-4 to analyze:
    • Candidate profile
    • Role requirements
    • Interview round context
  4. Generates:
    • Tailored interview questions
    • Expected answers
    • A summarized interview prep report
  5. Sends the report directly to the hiring team via email (SMTP)

πŸ“ Google Drive Structure

πŸ“‚ Root Folder
β”œβ”€β”€ πŸ“ jd/                          # Stores all job descriptions in PDF format
β”‚   β”œβ”€β”€ Backend_Engineer.pdf
β”‚   β”œβ”€β”€ Azure_DevOps_Lead.pdf
β”‚   └── ...
└── πŸ“„ Positions (Google Sheet)    # Maps Job Role ↔ JD File Link

πŸ“ Sample Mapping Sheet:
Positions Sheet

Columns:

  • Job Role
  • Job Description File URL (pointing to PDF in jd/ folder)

πŸ› οΈ How to Set Up

Step 1: Configure API Integrations

  • βœ… Connect your OpenAI GPT-4 API Key
  • βœ… Enable Google Cloud APIs:
    • Google Sheets API (to read job roles)
    • Google Drive API (to access CV and JD files)
  • βœ… Set up SMTP credentials (for email delivery)

Step 2: Prepare Google Drive & Mapping Sheet

  1. Create a root folder on Google Drive
  2. Inside the root folder:
    • Create a folder named /jd/ and upload all job descriptions (PDFs)
  3. 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:

  • πŸ“Ž Resume file (PDF)
  • 🧾 Job Role (dropdown)
  • πŸ”„ Interview Round (dropdown)

Step 4: Resume & JD Extraction

  • πŸ” Use Extract from PDF to parse the resume content
  • πŸ“„ Retrieve the JD link from the Positions sheet based on the selected Job Role
  • πŸ”— 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 6–8 tailored interview questions
    • Include expected answers and rationale

Step 7: Deliver Final Report

  • Format the content as:
    • πŸ“„ PDF (optional)
    • πŸ“¨ Email body
  • Send the report to the recruiter, hiring manager, or interviewer via SMTP

βœ… Requirements

  • πŸ”‘ OpenAI GPT-4 API Key
  • πŸ“ Google Drive (for resume and JD storage)
  • πŸ“Š Google Sheet (job role mapping)
  • πŸ“¬ SMTP credentials (host, username, password)
  • 🧰 n8n self-hosted or cloud instance with:
    • PDF Parser
    • Google Sheets node
    • HTTP Download node
    • Email node

✏️ 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

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 2 - Application form

Type / Role
n8n-nodes-base.formTrigger - formTrigger
Config choices
Version 2.2

Block 3 - Extract profile

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 4 - json parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 5 - gpt4-1 model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 6 - Get position JD

Type / Role
n8n-nodes-base.googleSheets - googleSheets
Config choices
Version 4.6

Block 7 - Download file

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 8 - Extract Job Description

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 9 - Profile Analyzer Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.1

Block 10 - gpt-4-1 model 2

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 11 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 12 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 13 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 14 - Interview round metadata

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 15 - Merge

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 16 - Transform output

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 17 - Structured Output Parser

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 18 - Build interview prep report

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 19 - Send interview prep report to hiring team

Type / Role
n8n-nodes-base.emailSend - emailSend
Config choices
Version 2.1

Block 20 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 21 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 22 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 23 - Interview Expert Agent

Type / Role
@n8n/n8n-nodes-langchain.chainLlm - chainLlm
Config choices
Version 1.5

Block 24 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Showing the first 24 of 26 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Generate tailored interview questions with GPT-4 based on CV, JD, and round
Complexity advanced
Nodes 26
Categories HR, Multimodal AI
Author Trung Tran
Published 01 Aug 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/6767/6767.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Generate tailored interview questions with GPT-4 based on CV, JD, and round do?

Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round Watch the demo video below: [![Watch the video](https://s3.ap southeast 1.amazonaws.com/automatewith.me/smart interview p...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your HR, Multimodal AI use case.