Pratyush Kumar Jha This workflow corresponds to n8n.io template #13507 — we link there as the canonical source.
This workflow follows the Agent → Form Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "6NgPkjl85BJqhJA5",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Smart Resume Screener \u2014 JD \u2194 Resume AI Match & Sheet Logger",
"tags": [],
"nodes": [
{
"id": "c32296bd-5d48-4b4e-93e1-d65871c27b4c",
"name": "Set Resume",
"type": "n8n-nodes-base.set",
"position": [
-848,
320
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "0f9e36f9-60cb-4593-a586-723124d69ff8",
"name": "resume",
"type": "string",
"value": "={{ $json.text }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "757ef828-06d7-4491-9232-b46838a8c337",
"name": "Recruiter Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-80,
336
],
"parameters": {
"text": "=Candidate Resume:\n{{ $json.data[0].resume }}\n",
"options": {
"systemMessage": "=# Overview\nYou are an expert recruiter. You have been given a job description and a candidate resume. Your task is to analyze the resume in relation to the job description and provide a detailed screening report. \n\nFocus specifically on how well the candidate matches the core requirements and ideal profile outlined in the job description. Evaluate both technical skill alignment and business-context understanding. Use reasoning grounded in the actual content of the resume and job post \u2014 avoid making assumptions.\n\n## Output\nYour output should follow this exact format:\n\nCandidate Strengths: \nList the top strengths or relevant qualifications the candidate brings to the table. Be specific.\n\nCandidate Weaknesses:\nList areas where the candidate is lacking or mismatched based on the job description.\n\nRisk Factor:\n- Assign a risk score (Low / Medium / High) \n- Explain the worst-case scenario if this candidate is hired.\n\nReward Factor: \n- Assign a reward score (Low / Medium / High) \n- Describe the best-case scenario \u2014 what value could this candidate unlock? \n- Does the candidate appear to be a short-term or long-term fit?\n\nOverall Fit Rating (0\u201310): \nAssign a number between 0 (terrible match) and 10 (perfect match). Do not give decimals.\n\nJustification for Rating:\nExplain clearly why this candidate received that score. Reference specific resume content and how it aligns or doesn't with the job description.\n\n## Job Description\n{{ $json.data[1].output['Job description'] }}\n\n"
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2
},
{
"id": "fdfaf5f0-4342-4a73-a3e3-508e18d73716",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
48,
160
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"name\": \"resume_screening_evaluation\",\n \"description\": \"Analyzes a candidate's resume against a job description and outputs strengths, weaknesses, risk/reward assessment, and an overall fit score.\",\n \"type\": \"object\",\n \"properties\": {\n \"candidate_strengths\": {\n \"type\": \"array\",\n \"description\": \"A list of specific strengths or qualifications that match the job description.\",\n \"items\": {\n \"type\": \"string\"\n }\n },\n \"candidate_weaknesses\": {\n \"type\": \"array\",\n \"description\": \"A list of areas where the candidate falls short or lacks alignment with the job requirements.\",\n \"items\": {\n \"type\": \"string\"\n }\n },\n \"risk_factor\": {\n \"type\": \"object\",\n \"description\": \"An evaluation of the potential risks of hiring this candidate.\",\n \"properties\": {\n \"score\": {\n \"type\": \"string\",\n \"enum\": [\"Low\", \"Medium\", \"High\"],\n \"description\": \"The risk level of hiring this candidate.\"\n },\n \"explanation\": {\n \"type\": \"string\",\n \"description\": \"A brief explanation of the worst-case scenario if the candidate is hired.\"\n }\n },\n \"required\": [\"score\", \"explanation\"]\n },\n \"reward_factor\": {\n \"type\": \"object\",\n \"description\": \"An evaluation of the potential upside of hiring this candidate.\",\n \"properties\": {\n \"score\": {\n \"type\": \"string\",\n \"enum\": [\"Low\", \"Medium\", \"High\"],\n \"description\": \"The reward level of hiring this candidate.\"\n },\n \"explanation\": {\n \"type\": \"string\",\n \"description\": \"A description of the best-case scenario and whether the candidate is a short-term or long-term fit.\"\n }\n },\n \"required\": [\"score\", \"explanation\"]\n },\n \"overall_fit_rating\": {\n \"type\": \"integer\",\n \"description\": \"A rating from 0 to 10 indicating how well the candidate matches the job description.\",\n \"minimum\": 0,\n \"maximum\": 10\n },\n \"justification_for_rating\": {\n \"type\": \"string\",\n \"description\": \"A summary explaining why the candidate received the specific fit rating, referencing resume and job description alignment.\"\n }\n },\n \"required\": [\n \"candidate_strengths\",\n \"candidate_weaknesses\",\n \"risk_factor\",\n \"reward_factor\",\n \"overall_fit_rating\",\n \"justification_for_rating\"\n ]\n}\n"
},
"typeVersion": 1.3
},
{
"id": "4de5dbd7-385b-488e-9926-b3a1856eec57",
"name": "Information Extractor",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
384,
336
],
"parameters": {
"text": "={{ $('Set Resume').item.json.resume }}",
"options": {},
"attributes": {
"attributes": [
{
"name": "First Name",
"required": true,
"description": "first name of the candidate"
},
{
"name": "Last Name",
"required": true,
"description": "last name of the candidate"
},
{
"name": "Email Address",
"required": true,
"description": "candidate's email address"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "e2038b38-cfd0-41da-be93-75fc2e456789",
"name": "Append Data",
"type": "n8n-nodes-base.googleSheets",
"position": [
736,
336
],
"parameters": {
"columns": {
"value": {
"Date": "={{ $now.format('yyyy-MM-dd hh:m a') }}",
"Email": "={{ $json.output['Email Address'] }}",
"Last Name": "={{ $json.output['Last Name'] }}",
"Strengths": "={{ $('Recruiter Agent').item.json.output.candidate_strengths.join(\"\\n\\n\") }}",
"First Name": "={{ $json.output['First Name'] }}",
"Weaknesses": "={{ $('Recruiter Agent').item.json.output.candidate_weaknesses.join(\"\\n\\n\") }}",
"Overall Fit": "={{ $('Recruiter Agent').item.json.output.overall_fit_rating }}",
"Risk Factor": "={{ $('Recruiter Agent').item.json.output.risk_factor.score }}\n\n{{ $('Recruiter Agent').item.json.output.risk_factor.explanation }}",
"Justification": "={{ $('Recruiter Agent').item.json.output.justification_for_rating }}",
"Reward Factor": "={{ $('Recruiter Agent').item.json.output.reward_factor.score }}\n\n{{ $('Recruiter Agent').item.json.output.reward_factor.explanation }}"
},
"schema": [
{
"id": "Date",
"type": "string",
"display": true,
"required": false,
"displayName": "Date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "First Name",
"type": "string",
"display": true,
"required": false,
"displayName": "First Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Last Name",
"type": "string",
"display": true,
"required": false,
"displayName": "Last Name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Email",
"type": "string",
"display": true,
"required": false,
"displayName": "Email",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Strengths",
"type": "string",
"display": true,
"required": false,
"displayName": "Strengths",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Weaknesses",
"type": "string",
"display": true,
"required": false,
"displayName": "Weaknesses",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Risk Factor",
"type": "string",
"display": true,
"required": false,
"displayName": "Risk Factor",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Reward Factor",
"type": "string",
"display": true,
"required": false,
"displayName": "Reward Factor",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Overall Fit",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Overall Fit",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Justification",
"type": "string",
"display": true,
"required": false,
"displayName": "Justification",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs/edit#gid=0",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs/edit?usp=drivesdk",
"cachedResultName": " Resume Screener"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.6
},
{
"id": "a471ca58-f0b5-4c0d-93c7-ac2a3ab958dd",
"name": "Extract from File2",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-1440,
176
],
"parameters": {
"options": {},
"operation": "pdf",
"binaryPropertyName": "=Resume"
},
"typeVersion": 1
},
{
"id": "11960013-de20-4f1e-95ce-872cce293c69",
"name": "On form submission",
"type": "n8n-nodes-base.formTrigger",
"position": [
-1664,
336
],
"parameters": {
"options": {},
"formTitle": "Check Your Resume Score",
"formFields": {
"values": [
{
"fieldType": "file",
"fieldLabel": "Resume",
"requiredField": true
},
{
"fieldLabel": "Job Description Link",
"requiredField": true
}
]
}
},
"typeVersion": 2.3
},
{
"id": "470a4835-b9a5-4eb6-ab62-306e155e6bc2",
"name": "HTTP Request",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1440,
336
],
"parameters": {
"url": "={{ $json['Job Description Link'] }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "3680f0a7-4a91-47ef-8c47-f203ea941d52",
"name": "Information Extractor1",
"type": "@n8n/n8n-nodes-langchain.informationExtractor",
"position": [
-1232,
336
],
"parameters": {
"text": "={{ $json.data }}",
"options": {},
"attributes": {
"attributes": [
{
"name": "Job description",
"required": true,
"description": "Job description"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "1febc5bc-879b-4608-bf78-b380df273299",
"name": "Merge",
"type": "n8n-nodes-base.merge",
"position": [
-528,
336
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "40278ccc-d227-4b14-9e16-265443836f2a",
"name": "Aggregate",
"type": "n8n-nodes-base.aggregate",
"position": [
-304,
336
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "0dd33d75-e6ef-49e0-beb9-fb920680d0ae",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2256,
-32
],
"parameters": {
"width": 454,
"height": 1328,
"content": "# Smart Resume Screener \u2014 JD \u2194 Resume AI Match & Sheet Logger\n\nSmart Resume Screener ingests a candidate resume and a job description link, extracts clean text from both, runs an LLM-powered screening agent to produce a structured assessment (strengths, weaknesses, risk/reward, justification, and a 0\u201310 fit score), extracts contact details, and appends a single, validated row to a Google Sheet for tracking.\n\n---\n\n# How It Works (Step-by-Step)\n\n## 1. Trigger \u2014 On Form Submission\n\n## 2. Extract & Fetch Content\n\n## 3. Prepare and Aggregate\n\n## 4. AI Evaluation\n\n## 5. Identity Extraction & Logging\n\n## 6. (Optional) Notifications / Follow-Ups\n\n# Quick Setup Guide\n\ud83d\udc49 [Demo & Setup Video](https://drive.google.com/file/d/11YmCsQhNmDaF_O_LoTvDV4gxCbPMOGJt/view?usp=sharing)\n\ud83d\udc49 [Sheet Template](https://docs.google.com/spreadsheets/d/1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs/edit?usp=sharing)\n\ud83d\udc49 [Course](https://www.udemy.com/course/n8n-automation-mastery-build-ai-powered-enterprise-ready/?referralCode=2EAE71591D3BEB80F2CC)\n"
},
"typeVersion": 1
},
{
"id": "174dac47-8d79-43d8-92e7-eb03484338a0",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
-528,
192
],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "bb39d3db-781e-41ff-ba55-7be8e29cef14",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1728,
-32
],
"parameters": {
"color": 6,
"width": 784,
"height": 544,
"content": "# Data Ingestion & Content Extraction\n## Collect candidate inputs and convert everything into structured, usable text."
},
"typeVersion": 1
},
{
"id": "e9e07857-66be-400d-983f-7babf59e6aee",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-912,
-32
],
"parameters": {
"color": 6,
"width": 1120,
"height": 544,
"content": "# AI Evaluation & Structured Screening\n## Evaluate candidate suitability using an AI recruiter agent."
},
"typeVersion": 1
},
{
"id": "56739da7-7238-4112-97ee-83fe762a756f",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
256,
-32
],
"parameters": {
"color": 6,
"width": 688,
"height": 544,
"content": "# Data Structuring & Recruitment Logging\n## Extract candidate identity details and log final screening data."
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "3cd5ce36-ed29-443d-84aa-f495387288b6",
"connections": {
"Merge": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Recruiter Agent",
"type": "main",
"index": 0
}
]
]
},
"Set Resume": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Information Extractor1",
"type": "main",
"index": 0
}
]
]
},
"Recruiter Agent": {
"main": [
[
{
"node": "Information Extractor",
"type": "main",
"index": 0
}
]
]
},
"Extract from File2": {
"main": [
[
{
"node": "Set Resume",
"type": "main",
"index": 0
}
]
]
},
"On form submission": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
},
{
"node": "Extract from File2",
"type": "main",
"index": 0
}
]
]
},
"Information Extractor": {
"main": [
[
{
"node": "Append Data",
"type": "main",
"index": 0
}
]
]
},
"Information Extractor1": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Information Extractor1",
"type": "ai_languageModel",
"index": 0
},
{
"node": "Recruiter Agent",
"type": "ai_languageModel",
"index": 0
},
{
"node": "Information Extractor",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Recruiter Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googlePalmApigoogleSheetsOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Smart Resume Screener ingests a candidate resume and a job description link, extracts clean text from both, runs an LLM-powered screening agent to produce a structured assessment (strengths, weaknesses, risk/reward, justification, and a 0–10 fit score), extracts contact details,…
Source: https://n8n.io/workflows/13507/ — original creator credit. Request a take-down →
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