Match job descriptions with resumes using Google Gemini and log scores to Google Sheets Workflow Solution

Workflow overview

Why this workflow matters

Relevant for managed services and support workflows. Supports knowledge capture and document intelligence use cases.

Smart Resume Screener — JD ↔ Resume AI Match & Sheet Logger 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, and appends a single, validated row to a Google Sheet for tracking. How It Works (Step-by-Step) 1. Trigger — On Form Submission Public form webhook sends: Binary resume file (PDF / DOCX) Job Description (JD) URL or text 2. Extract & Fetch Content Resume Extraction node** Converts the uploaded binary resume into plain text (data.resume). HTTP Request node** Fetches the JD HTML/text from the provided link. Job Description Extractor (LLM-driven)** Parses the fetched content into structured JD fields: Requirements Responsibilities Skills Seniority etc. 3. Prepare and Aggregate Set Resume node** Normalizes the resume into a clean JSON object. Merge/Aggregate node** Builds a single payload containing: { "resume": "...", "job_description": "...", "meta": "..." } 4. AI Evaluation Recruiter Agent (LangChain node, powered by Google Gemini)** Receives aggregated payload Returns a strict JSON-formatted screening report including: candidate_strengths candidate_weaknesses risk reward overall_fit_rating (0–10 numeric) justification Structured Output Parser** Enforces JSON schema Ensures predictable downstream data 5. Identity Extraction & Logging Contact Info Extractor** Extracts: Name Email Append to Google Sheets** Writes: Date Name Email Strengths Weaknesses Risk Reward Justification Overall Fit Score 6. (Optional) Notifications / Follow-Ups Add Slack / Email / Webhook nodes Trigger alerts for high-fit candidates Quick Setup Guide 👉 Demo & Setup Video 👉 Sheet Template 👉 Course Nodes of Interest You Can Edit Trigger — On Form Submission Change webhook URL Modify accepted form fields Add metadata capture (job_id, source) Resume Extraction (Extract from File) Enable OCR fallback Adjust encoding/charset handling Replace with third-party resume parser HTTP Request (Fetch Job Description) Configure timeouts Add retry policy Set headers Restrict allowed domains Job Description Extractor (Information Extractor1) Modify extractor prompt/schema Add fields like must_have and nice_to_have Set Resume (Prepare Resume) Strip headers/footers Normalize dates Split resume sections Merge / Aggregate Modify payload structure Add context fields (job_id, recruiter_notes, source_platform) Recruiter Agent (LangChain Agent) Edit system/user prompts Adjust model temperature Modify token limits Switch LLM provider Structured Output Parser Update JSON schema Add fields like: experience_years certifications notice_period Contact Info Extractor Add: Phone LinkedIn Location Append to Google Sheets Modify column mapping Add fields like: workflow_run_id resume_link What You’ll Need (Credentials) Google Sheets API credentials (OAuth or Service Account) Google Drive / Storage credentials (if resumes are stored there) LLM provider credentials (e.g., Google Gemini API key/service account) (Optional) OCR / Vision API credentials for scanned PDFs (Optional) Email / Slack / Teams webhook or SMTP credentials Access to public JD URLs (or credentials if behind authentication) Recommended Settings & Best Practices LLM temperature:** 0.0–0.3 for consistent output Max tokens:** 800–1200 for justification (with enforced limits) Strict JSON schema:** Fail fast on invalid structure Retries & timeouts:** ~10s HTTP timeout 2 retries with exponential backoff Rate limiting:** Protect LLM quotas Deduplication:** Check existing email or resume hash Least privilege:** Scope Google service account to target sheet only PII handling:** Limit exposed fields; encrypt sensitive data if needed Schema versioning:** Add schema_version column Error logging:** Use Catch node with workflow_run_id Human review gate:** Route borderline scores (6–7) for manual review Customization Ideas Conditional alerts (overall_fit_rating >= 8) Multi-model scoring (Gemini + alternative model) Automated outreach emails ATS integration (Greenhouse, Lever, etc.) JD template library Multi-language resume routing Skill-level mapping (e.g., python: 4/5) Candidate scoring dashboard Resume storage with secure links Troubleshooting — Quick Tips Resume Extraction Issues Validate binary input Enable OCR for scanned PDFs Check encoding and file type JD Fetch Failure Validate URL reachability Add headers (User-Agent) Increase timeout Provide auth if needed LLM JSON Errors Lower temperature (0–0.2) Enforce strict JSON prompt Add retry with "fix-json" prompt Inspect raw LLM output Google Sheets Append Fails Check credential expiry Confirm sheet ID and gid Validate column mapping Monitor API quota Duplicate Rows Add email-based dedupe logic Hash resume content PII Exposure Audit sheet sharing settings Use restricted service accounts Tags / Suggested Listing Fields recruiting resume-parser ai-screening langchain google-gemini google-sheets AlekSystem ats-integration pii-sensitive automation

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