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Audit Interview Feedback & Report via Slack with GPT-4o-mini and Google Sheets

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Created by: Rahul Joshi || rahul08

Rahul Joshi

Last update

Last update 21 hours ago

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Description

This workflow automates the evaluation of interviewer feedback using AI. It retrieves raw notes from Google Sheets, processes them through GPT-4o-mini for structured scoring, validates outputs, and calculates weighted quality scores. The system provides real-time Slack feedback to interviewers, logs AI errors for transparency, and recommends training if the feedback quality is low.

What This Template Does (Step-by-Step)

  • ⚡ Manual Trigger – Runs the workflow manually to start evaluation.
  • 📋 Fetch Raw Feedback Data (Google Sheets) – Reads all feedback entries (Role, Stage, Interviewer Email, Feedback Text, row_number).
  • 🧠 AI Quality Evaluator (Azure GPT-4o-mini) – Processes feedback into structured JSON across 5 dimensions.
  • 🔍 Analyze Feedback Quality (LLM Chain) – Applies scoring rules (Specificity, STAR, Bias-Free, Actionability, Depth) and outputs structured JSON.
  • ✅ Validate AI Response – Ensures AI output isn’t undefined or malformed.
  • 🚨 Log AI Errors (Google Sheets) – Records invalid AI responses for debugging and auditing.
  • 🔄 Parse AI JSON Output (Code Node) – Converts AI JSON text into structured n8n objects with error handling.
  • 🧮 Calculate Weighted Quality Score (Code Node) – Computes final weighted score (0–100), generates flags, formats vague phrases, and preserves context.
  • 💾 Save Scores to Spreadsheet (Google Sheets) – Updates the original feedback row with Score, Flags, and AI JSON.
  • 💬 Send Feedback Summary to Interviewer (Slack) – Sends interviewers a structured Slack report (score, flags, vague phrases, STAR improvement tips).
  • 🎯 Check if Training Needed – Applies threshold logic: if score < 50, route to training recommendations.
  • 📚 Send Training Recommendations (Slack) – Delivers STAR method guides and bias-free interviewing resources to low scorers.

Prerequisites

  • Google Sheets (Raw_Feedback + Error Log Sheet)
  • Azure OpenAI API credentials (for GPT-4o-mini)
  • Slack API credentials (for sending feedback & training notifications)
  • n8n instance (cloud or self-hosted)

Key Benefits

✅ Automated interview feedback quality scoring
✅ Bias detection and vague feedback flagging
✅ Real-time Slack feedback to interviewers
✅ Error logging for AI reliability tracking
✅ Training recommendations for low scorers
✅ Audit trail maintained in Google Sheets

Perfect For

  • HR & Recruitment teams ensuring structured interviewer feedback
  • Organizations enforcing STAR method & bias-free hiring
  • Teams seeking continuous interviewer coaching
  • Companies needing audit-ready records of interview quality