{"workflow":{"id":13507,"name":"Match job descriptions with resumes using Google Gemini and log scores to Google Sheets","views":103,"recentViews":0,"totalViews":103,"createdAt":"2026-02-19T07:11:53.223Z","description":"# Smart Resume Screener — JD ↔ 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 0–10 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 — On Form Submission\nPublic form webhook sends:\n- Binary resume file (PDF / DOCX)\n- Job Description (JD) URL or text\n\n---\n\n## 2. Extract & Fetch Content\n\n- **Resume Extraction node**\n  - Converts the uploaded binary resume into plain text (`data.resume`).\n\n- **HTTP Request node**\n  - Fetches the JD HTML/text from the provided link.\n\n- **Job Description Extractor (LLM-driven)**\n  - Parses the fetched content into structured JD fields:\n    - Requirements\n    - Responsibilities\n    - Skills\n    - Seniority\n    - etc.\n\n---\n\n## 3. Prepare and Aggregate\n\n- **Set Resume node**\n  - Normalizes the resume into a clean JSON object.\n\n- **Merge/Aggregate node**\n  - Builds a single payload containing:\n    ```json\n    { \"resume\": \"...\", \"job_description\": \"...\", \"meta\": \"...\" }\n    ```\n\n---\n\n## 4. AI Evaluation\n\n- **Recruiter Agent (LangChain node, powered by Google Gemini)**\n  - Receives aggregated payload\n  - Returns a strict JSON-formatted screening report including:\n\n    - `candidate_strengths`\n    - `candidate_weaknesses`\n    - `risk`\n    - `reward`\n    - `overall_fit_rating` (0–10 numeric)\n    - `justification`\n\n- **Structured Output Parser**\n  - Enforces JSON schema\n  - Ensures predictable downstream data\n\n---\n\n## 5. Identity Extraction & Logging\n\n- **Contact Info Extractor**\n  - Extracts:\n    - Name\n    - Email\n\n- **Append to Google Sheets**\n  - Writes:\n    - Date\n    - Name\n    - Email\n    - Strengths\n    - Weaknesses\n    - Risk\n    - Reward\n    - Justification\n    - Overall Fit Score\n\n---\n\n## 6. (Optional) Notifications / Follow-Ups\n\n- Add Slack / Email / Webhook nodes\n- Trigger alerts for high-fit candidates\n\n---\n\n# Quick Setup Guide\n👉 [Demo & Setup Video](https://drive.google.com/file/d/11YmCsQhNmDaF_O_LoTvDV4gxCbPMOGJt/view?usp=sharing)\n👉 [Sheet Template](https://docs.google.com/spreadsheets/d/1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs/edit?usp=sharing)\n👉 [Course](https://www.udemy.com/course/n8n-automation-mastery-build-ai-powered-enterprise-ready/?referralCode=2EAE71591D3BEB80F2CC)\n\n\n# Nodes of Interest You Can Edit\n\n## Trigger — On Form Submission\n- Change webhook URL\n- Modify accepted form fields\n- Add metadata capture (`job_id`, `source`)\n\n## Resume Extraction (Extract from File)\n- Enable OCR fallback\n- Adjust encoding/charset handling\n- Replace with third-party resume parser\n\n## HTTP Request (Fetch Job Description)\n- Configure timeouts\n- Add retry policy\n- Set headers\n- Restrict allowed domains\n\n## Job Description Extractor (Information Extractor1)\n- Modify extractor prompt/schema\n- Add fields like `must_have` and `nice_to_have`\n\n## Set Resume (Prepare Resume)\n- Strip headers/footers\n- Normalize dates\n- Split resume sections\n\n## Merge / Aggregate\n- Modify payload structure\n- Add context fields (`job_id`, `recruiter_notes`, `source_platform`)\n\n## Recruiter Agent (LangChain Agent)\n- Edit system/user prompts\n- Adjust model temperature\n- Modify token limits\n- Switch LLM provider\n\n## Structured Output Parser\n- Update JSON schema\n- Add fields like:\n  - `experience_years`\n  - `certifications`\n  - `notice_period`\n\n## Contact Info Extractor\n- Add:\n  - Phone\n  - LinkedIn\n  - Location\n\n## Append to Google Sheets\n- Modify column mapping\n- Add fields like:\n  - `workflow_run_id`\n  - `resume_link`\n\n---\n\n# What You’ll Need (Credentials)\n\n- Google Sheets API credentials (OAuth or Service Account)\n- Google Drive / Storage credentials (if resumes are stored there)\n- LLM provider credentials (e.g., Google Gemini API key/service account)\n- (Optional) OCR / Vision API credentials for scanned PDFs\n- (Optional) Email / Slack / Teams webhook or SMTP credentials\n- Access to public JD URLs (or credentials if behind authentication)\n\n---\n\n# Recommended Settings & Best Practices\n\n- **LLM temperature:** 0.0–0.3 for consistent output\n- **Max tokens:** 800–1200 for justification (with enforced limits)\n- **Strict JSON schema:** Fail fast on invalid structure\n- **Retries & timeouts:**\n  - ~10s HTTP timeout\n  - 2 retries with exponential backoff\n- **Rate limiting:** Protect LLM quotas\n- **Deduplication:** Check existing email or resume hash\n- **Least privilege:** Scope Google service account to target sheet only\n- **PII handling:** Limit exposed fields; encrypt sensitive data if needed\n- **Schema versioning:** Add `schema_version` column\n- **Error logging:** Use Catch node with `workflow_run_id`\n- **Human review gate:** Route borderline scores (6–7) for manual review\n\n---\n\n# Customization Ideas\n\n- Conditional alerts (`overall_fit_rating >= 8`)\n- Multi-model scoring (Gemini + alternative model)\n- Automated outreach emails\n- ATS integration (Greenhouse, Lever, etc.)\n- JD template library\n- Multi-language resume routing\n- Skill-level mapping (e.g., `python: 4/5`)\n- Candidate scoring dashboard\n- Resume storage with secure links\n\n---\n\n# Troubleshooting — Quick Tips\n\n## Resume Extraction Issues\n- Validate binary input\n- Enable OCR for scanned PDFs\n- Check encoding and file type\n\n## JD Fetch Failure\n- Validate URL reachability\n- Add headers (User-Agent)\n- Increase timeout\n- Provide auth if needed\n\n## LLM JSON Errors\n- Lower temperature (0–0.2)\n- Enforce strict JSON prompt\n- Add retry with \"fix-json\" prompt\n- Inspect raw LLM output\n\n## Google Sheets Append Fails\n- Check credential expiry\n- Confirm sheet ID and gid\n- Validate column mapping\n- Monitor API quota\n\n## Duplicate Rows\n- Add email-based dedupe logic\n- Hash resume content\n\n## PII Exposure\n- Audit sheet sharing settings\n- Use restricted service accounts\n\n---\n\n# Tags / Suggested Listing Fields\n\n- recruiting  \n- resume-parser  \n- ai-screening  \n- langchain  \n- google-gemini  \n- google-sheets  \n- n8n  \n- ats-integration  \n- pii-sensitive  \n- automation  \n","workflow":{"id":"6NgPkjl85BJqhJA5","meta":{"instanceId":"4764540811cbb8d2e1efff249fe019f120efdfc1d1ad5d0e40382bf91ca0b3dc","templateCredsSetupCompleted":true},"name":"Smart Resume Screener — JD ↔ 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 — 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 — what value could this candidate unlock?  \n- Does the candidate appear to be a short-term or long-term fit?\n\nOverall Fit Rating (0–10):  \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 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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":{"id":"mAQcaPLUUl8WFD1j","name":"Google Sheets account"}},"typeVersion":4.6},{"id":"a471ca58-f0b5-4c0d-93c7-ac2a3ab958dd","name":"Extract from 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}}","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 — JD ↔ 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 0–10 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 — 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👉 [Demo & Setup Video](https://drive.google.com/file/d/11YmCsQhNmDaF_O_LoTvDV4gxCbPMOGJt/view?usp=sharing)\n👉 [Sheet Template](https://docs.google.com/spreadsheets/d/1_a0HFGiv-D7_WqlmrL50CGrTW5W_8QeKW-YqbmdBjSs/edit?usp=sharing)\n👉 [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":{"id":"scf4DJDBt8eBly6x","name":"Google Gemini Api account"}},"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,"pinData":{},"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}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":16,"nodeTypes":{"n8n-nodes-base.set":{"count":1},"n8n-nodes-base.merge":{"count":1},"n8n-nodes-base.aggregate":{"count":1},"n8n-nodes-base.stickyNote":{"count":4},"n8n-nodes-base.formTrigger":{"count":1},"n8n-nodes-base.httpRequest":{"count":1},"n8n-nodes-base.googleSheets":{"count":1},"@n8n/n8n-nodes-langchain.agent":{"count":1},"n8n-nodes-base.extractFromFile":{"count":1},"@n8n/n8n-nodes-langchain.lmChatGoogleGemini":{"count":1},"@n8n/n8n-nodes-langchain.informationExtractor":{"count":2},"@n8n/n8n-nodes-langchain.outputParserStructured":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"Pratyush Kumar Jha","username":"pratyush","bio":"Automation consultant specialising in n8n workflows. 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