Block 1 - Sticky Note1
- Type / Role
- n8n-nodes-base.stickyNote - stickyNote
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
Try It Out, HireMind – AI Driven Resume Intelligence Pipeline! This n8n template demonstrates how to automate resume screening and evaluation using AI to improve candidate processing and reduce man...
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.chainllm
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Trung Tran.
Original n8n.io sourceA smart and reliable resume screening pipeline for modern HR teams. This workflow combines Google Drive (JD & CV storage), OpenAI (GPT-4-based evaluation), Google Sheets (position mapping + result log), and Slack/SendGrid integrations for real-time communication. Automatically extract, evaluate, and track candidate applications with clarity and consistency.
├── jd # Google drive folder to store your JD (pdf)
│ ├── Backend_Engineer.pdf
│ ├── Azure_DevOps_Lead.pdf
│ └── ...
│
├── cv # Google drive folder, where workflow upload candidate resume
│ ├── John_Doe_DevOps.pdf
│ ├── Jane_Smith_FullStack.pdf
│ └── ...
│
├── Positions (Sample: https://docs.google.com/spreadsheets/d/1pW0muHp1NXwh2GiRvGVwGGRYCkcMR7z8NyS9wvSPYjs/edit?usp=sharing) # 📋 Mapping Table: Job Role ↔ Job Description (Link)
│ └── Columns:
│ - Job Role
│ - Job Description File URL (PDF in jd/)
│
└── Evaluation form (Google Sheet) # ✅ Final AI Evaluation Results
Set up credentials and integrations:
Prepare your Google Drive structure:
/jd → Store all job descriptions in PDF format /cv → This is where candidate CVs will be uploaded automaticallyPositions with the following structure:| Job Role | Job Description Link |
|------------------------------|----------------------------------------|
| Azure DevOps Engineer | https://drive.google.com/xxx/jd1.pdf |
| Full-Stack Developer (.NET) | https://drive.google.com/xxx/jd2.pdf |
Update your application form:
Positions sheetRun the AI workflow:
/cv folder/jdDistribute and store results:
Evaluation form Google SheetJoin the n8n Discord or ask in the n8n Forum!
Happy Hiring! 🚀
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.
Showing the first 24 of 26 workflow blocks. Download the JSON for the full node graph.
| Workflow | AI resume screening & evaluation for HR with GPT-4 & Google Workspace |
|---|---|
| Complexity | advanced |
| Nodes | 26 |
| Categories | HR, AI Summarization |
| Author | Trung Tran |
| Published | 29 Jul 2025 |
Use the JSON export at /data/workflows/6612/6612.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
Try It Out, HireMind – AI Driven Resume Intelligence Pipeline! This n8n template demonstrates how to automate resume screening and evaluation using AI to improve candidate processing and reduce man...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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, AI Summarization use case.