{
  "workflow": {
    "id": 9139,
    "name": "Audit interview feedback & report via Slack with GPT-4o-mini and Google Sheets",
    "views": 63,
    "recentViews": 0,
    "totalViews": 63,
    "createdAt": "2025-10-01T07:26:44.866Z",
    "description": "## Description\nThis 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.\n## What This Template Does (Step-by-Step)\n- ⚡ Manual Trigger – Runs the workflow manually to start evaluation.\n-  📋 Fetch Raw Feedback Data (Google Sheets) – Reads all feedback entries (Role, Stage, Interviewer Email, Feedback Text, row_number).\n-  🧠 AI Quality Evaluator (Azure GPT-4o-mini) – Processes feedback into structured JSON across 5 dimensions.\n-  🔍 Analyze Feedback Quality (LLM Chain) – Applies scoring rules (Specificity, STAR, Bias-Free, Actionability, Depth) and outputs structured JSON.\n-  ✅ Validate AI Response – Ensures AI output isn’t undefined or malformed.\n-  🚨 Log AI Errors (Google Sheets) – Records invalid AI responses for debugging and auditing.\n-  🔄 Parse AI JSON Output (Code Node) – Converts AI JSON text into structured n8n objects with error handling.\n-  🧮 Calculate Weighted Quality Score (Code Node) – Computes final weighted score (0–100), generates flags, formats vague phrases, and preserves context.\n-  💾 Save Scores to Spreadsheet (Google Sheets) – Updates the original feedback row with Score, Flags, and AI JSON.\n-  💬 Send Feedback Summary to Interviewer (Slack) – Sends interviewers a structured Slack report (score, flags, vague phrases, STAR improvement tips).\n-  🎯 Check if Training Needed – Applies threshold logic: if score < 50, route to training recommendations.\n-  📚 Send Training Recommendations (Slack) – Delivers STAR method guides and bias-free interviewing resources to low scorers.\n\n## Prerequisites\n- Google Sheets (Raw_Feedback + Error Log Sheet)\n- Azure OpenAI API credentials (for GPT-4o-mini)\n- Slack API credentials (for sending feedback & training notifications)\n- n8n instance (cloud or self-hosted)\n\n## Key Benefits\n ✅ Automated interview feedback quality scoring\n ✅ Bias detection and vague feedback flagging\n ✅ Real-time Slack feedback to interviewers\n ✅ Error logging for AI reliability tracking\n ✅ Training recommendations for low scorers\n ✅ Audit trail maintained in Google Sheets\n\n## Perfect For\n- HR & Recruitment teams ensuring structured interviewer feedback\n- Organizations enforcing STAR method & bias-free hiring\n- Teams seeking continuous interviewer coaching\n- Companies needing audit-ready records of interview quality",
    "workflow": {
      "id": "DZrX6urOE53Tm4jp",
      "meta": {
        "instanceId": "8443f10082278c46aa5cf3acf8ff0f70061a2c58bce76efac814b16290845177",
        "templateCredsSetupCompleted": true
      },
      "name": "Interview Quality Audit",
      "tags": [],
      "nodes": [
        {
          "id": "9e228e13-31c4-4f40-8bc1-83ffc0c0df21",
          "name": "When clicking ‘Execute workflow’",
          "type": "n8n-nodes-base.manualTrigger",
          "position": [
            -176,
            16
          ],
          "parameters": {},
          "typeVersion": 1
        },
        {
          "id": "4656de9f-4ad6-4b48-a8b0-6802cd1e88ca",
          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            576,
            160
          ],
          "parameters": {
            "height": 384,
            "content": " ✅ Validate AI Response\nType: Conditional Logic\nPurpose: Quality control checkpoint\nValidation:\n\nResponse text is not undefined\nContains valid data structure\n\nRouting:\n\n✅ Valid → Continue to JSON parsing\n❌ Invalid → Log to error sheet\n\nFunction: Prevents malformed responses from corrupting pipeline"
          },
          "typeVersion": 1
        },
        {
          "id": "ed2e275a-ea76-4d78-b9da-2149ec9f5b50",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            224,
            352
          ],
          "parameters": {
            "height": 320,
            "content": "🤖 AI Quality Evaluator (GPT-4o)\nType: AI Language Model\nPurpose: Cognitive engine for feedback analysis\nConfiguration:\n\nModel: gpt-4o-mini\nPlatform: Azure OpenAI\nIntegration: LangChain\n\nConnects to Azure GPT-4o-mini\nPowers NLP evaluation\nGenerates structured JSON outputs"
          },
          "typeVersion": 1
        },
        {
          "id": "97cdbdb7-5306-4910-8e93-927940ed699d",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            224,
            -560
          ],
          "parameters": {
            "width": 336,
            "height": 544,
            "content": "🔍 Analyze Feedback Quality\nType: LangChain LLM Chain\nPurpose: Core AI evaluation engine\nEvaluation Dimensions (1-5 Scale):\n\nSpecificity (35%) - Concrete details\nStructure/STAR (15%) - Situation-Task-YOUR_OPENAI_KEY_HERE-Result\nBias-Free Language (15%) - No gender/appearance bias\nActionability (10%) - Decision usefulness\nDepth (25%) - Multiple competencies\n\nScoring:\n\n5: Excellent - Clear STAR with evidence\n3: Adequate - Some info but vague\n1: Unusable - Purely subjective\n\nSpecial Rules:\n\nFeedback <30 words → Scores ≤2\nExtracts vague phrases (\"great guy\", \"nice energy\")\n\nOutput: JSON with scores and vague_phrases array"
          },
          "typeVersion": 1
        },
        {
          "id": "6681d513-9520-4c78-8595-cbb27bdfff9c",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -64,
            192
          ],
          "parameters": {
            "height": 368,
            "content": "📋 Fetch Interview Feedback\nType: Google Sheets Read\nPurpose: Retrieve raw feedback data\nConfiguration:\n\nDocument: Interviewer Brief Pack\nSheet: Raw_Feedback\nOperation: Read all rows\n\nData Retrieved:\nTimestamp, Candidate_ID, Role, Stage, Interviewer_Email, Feedback_Text, row_number\nOutput: All feedback records passed to AI evaluation"
          },
          "typeVersion": 1
        },
        {
          "id": "f3e8a974-86fa-4a81-a5bd-3cbebf6302b4",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            928,
            -224
          ],
          "parameters": {
            "width": 288,
            "height": 208,
            "content": "🔄 Parse AI JSON Output\nType: JavaScript Code\nPurpose: Convert string to structured data\nFunction:\n\nSafely parses AI text to JSON object\nTry-catch error handling\nThrows descriptive errors for debugging"
          },
          "typeVersion": 1
        },
        {
          "id": "78deb6fe-c12f-4281-974d-19a9155f0f0e",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1664,
            448
          ],
          "parameters": {
            "width": 320,
            "height": 224,
            "content": "🎯 Check if Training Needed\nType: Conditional Logic\nPurpose: Identify low performers\nCondition: Score < 50\nRouting:\n\n✅ <50 → Send training resources\n❌ ≥50 → No additional action\n\nFunction: Triggers enhanced coaching for scores below threshold"
          },
          "typeVersion": 1
        },
        {
          "id": "97e18f0a-359c-4bf3-8ff8-bfe51a193e7d",
          "name": "Sticky Note6",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            2064,
            464
          ],
          "parameters": {
            "width": 400,
            "height": 304,
            "content": "📚 Send Training Recommendations\nType: Slack Notification\nPurpose: Deliver coaching resources\nMessage Content:\n\nScore, Flags, Specific vague phrases\nImprovement guidance (STAR method)\n📘 STAR Method Guide link\n🎥 Bias-Free Interviewing Video link\n\nFunction:\n\nDetailed coaching for scores <50\nLinks to training resources\nSupportive, growth-focused tone"
          },
          "typeVersion": 1
        },
        {
          "id": "b88c8198-7941-41a6-8b7f-406f62371288",
          "name": "Sticky Note7",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            880,
            464
          ],
          "parameters": {
            "height": 320,
            "content": "🚨 Log AI Errors\nType: Google Sheets Append\nPurpose: Error tracking\nConfiguration:\n\nSheet: error log sheet\nOperation: APPEND\n\nFunction:\n\nCaptures AI failures\nCreates error audit trail\nEnables debugging and monitoring\nTracks system reliability\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "a98fbf8e-388a-40fe-a7a7-5e54866da422",
          "name": "Sticky Note9",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1808,
            -144
          ],
          "parameters": {
            "width": 336,
            "height": 304,
            "content": "💬 Send Feedback Summary\nType: Slack Notification\nPurpose: Deliver quality report\nMessage Structure:\n\nRole, Stage, Score (X/100), Flags\nHigh Quality: Congratulations message\nNeeds Improvement: Vague phrases + STAR tips\n\nFunction:\n\nImmediate feedback to interviewer\nSpecific, actionable guidance\nEncourages continuous improvement"
          },
          "typeVersion": 1
        },
        {
          "id": "989baf43-960a-4393-9640-02b4454289d3",
          "name": "Sticky Note10",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1488,
            -592
          ],
          "parameters": {
            "width": 352,
            "height": 336,
            "content": "💾 Save Scores to Spreadsheet\nType: Google Sheets Update\nPurpose: Persist quality metrics\nConfiguration:\n\nSheet: Raw_Feedback\nOperation: UPDATE (match by row_number)\n\nFields Updated:\n\nScore (0-100)\nFlags (quality issues)\nLLM_JSON (complete AI analysis)\n\nFunction: Updates original rows, creates audit trail for trend analysis"
          },
          "typeVersion": 1
        },
        {
          "id": "c7fbcc25-cdde-4b02-b4ec-afdae31fff2e",
          "name": "Sticky Note11",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1152,
            160
          ],
          "parameters": {
            "width": 288,
            "height": 480,
            "content": "🧮 Calculate Weighted Quality Score\nType: JavaScript Code\nPurpose: Compute final score and flags\nWeights:\nSpecificity 35% | Depth 25% | Structure 15% | Bias-Free 15% | Actionability 10%\nFlags:\n\n\"low_detail\": specificity < 3 OR depth < 3\n\"bias\": bias_free_language < 3\n\nFunction:\n\nCalculates 0-100 score\nGenerates quality flags\nFormats vague phrases for Slack\nPreserves context (Role, Stage, row_number)\n\nOutput: Score, Flags, LLM_JSON, VaguePhrasesFormatted"
          },
          "typeVersion": 1
        },
        {
          "id": "69339a87-95fa-4827-a768-a6a9aa1def9e",
          "name": "Fetch Raw Feedback Data",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
            32,
            16
          ],
          "parameters": {
            "options": {},
            "sheetName": {
              "__rl": true,
              "mode": "list",
              "value": 315277036,
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y/edit#gid=315277036",
              "cachedResultName": "Raw_Feedback"
            },
            "documentId": {
              "__rl": true,
              "mode": "list",
              "value": "1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y/edit?usp=drivesdk",
              "cachedResultName": "Interviewer Brief Pack "
            }
          },
          "credentials": {
            "googleSheetsOAuth2Api": {
              "id": "credential-id",
              "name": "googleSheetsOAuth2Api Credential"
            }
          },
          "typeVersion": 4.6,
          "alwaysOutputData": false
        },
        {
          "id": "99814f2b-ab97-49bf-8eec-43083f731dad",
          "name": "AI Quality Evaluator (GPT-4o1",
          "type": "@n8n/n8n-nodes-langchain.lmChatAzureOpenAi",
          "position": [
            272,
            192
          ],
          "parameters": {
            "model": "gpt-4o-mini",
            "options": {}
          },
          "credentials": {
            "azureOpenAiApi": {
              "id": "credential-id",
              "name": "azureOpenAiApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "6517c215-19c5-4644-97f6-26d650c65540",
          "name": "Analyze Feedback Quality",
          "type": "@n8n/n8n-nodes-langchain.chainLlm",
          "position": [
            288,
            16
          ],
          "parameters": {
            "text": "=You are an Interview Feedback Quality Auditor.\n\nYour task is to evaluate interviewer feedback notes and score them across 5 dimensions:\n- specificity (1–5)\n- structure_STAR (1–5)\n- bias_free_language (1–5)\n- actionability (1–5)\n- depth (1–5)\n\n⚖️ Scoring Guidelines:\n- 5 = Excellent: Clear, detailed, STAR format (Situation, Task, Action, Result) explicitly used or strongly implied, with evidence/examples.\n- 4 = Good: Mostly structured, some detail, minor gaps, still useful for decisions.\n- 3 = Adequate: Some relevant info but mixed with vagueness, missing STAR elements.\n- 2 = Poor: Mostly vague or generic, no clear evidence, over-reliant on subjective phrasing.\n- 1 = Unusable: Purely subjective (“great guy”, “nice energy”), no actionable details.\n\nBias-free language: Score low if feedback references gender, looks, personality, or irrelevant traits.\n\nActionability: Score higher if the feedback directly helps in making a decision (e.g., “passed all test cases under time constraint” vs “seems smart”).\n\nDepth: Score higher if multiple competencies or dimensions are covered, lower if only 1 vague point.\n\n🚨 Additional Rules:\n- If text <30 words OR contains mostly emojis/placeholders → set ALL scores ≤2 and add `\"too_short\"` to vague_phrases.\n- Extract vague phrases (e.g., “good energy”, “smart guy”, “should be fine”) into `\"vague_phrases\"` array.\n\nReturn ONLY valid JSON in this schema:\n{\n  \"specificity\": <1–5>,\n  \"structure\": <1–5>,\n  \"bias_free_language\": <1–5>,\n  \"actionability\": <1–5>,\n  \"depth\": <1–5>,\n  \"vague_phrases\": [ ... ]\n}\n",
            "batching": {},
            "messages": {
              "messageValues": [
                {
                  "message": "You are an Interview Feedback Quality Auditor.   Evaluate interview feedback for specificity, structure (STAR), bias-free language, actionability, and depth.   Be strict but fair. Always return **only valid JSON** that follows the given schema.Return ONLY valid JSON, no explanations, no markdown, no quotes wrapping the whole object.\n"
                },
                {
                  "type": "HumanMessagePromptTemplate",
                  "message": "=Role: {{$json[\"Role\"]}}   Stage: {{$json[\"Stage\"]}}   Feedback: {{$json[\"Feedback_Text\"]}}"
                }
              ]
            },
            "promptType": "define"
          },
          "typeVersion": 1.7
        },
        {
          "id": "0612aeb7-a3a2-4215-9910-4cd077e06586",
          "name": "Validate AI Response",
          "type": "n8n-nodes-base.if",
          "position": [
            640,
            16
          ],
          "parameters": {
            "options": {},
            "conditions": {
              "options": {
                "version": 2,
                "leftValue": "",
                "caseSensitive": true,
                "typeValidation": "strict"
              },
              "combinator": "and",
              "conditions": [
                {
                  "id": "4901c65c-6aaf-4efe-a133-1fedfedc0bca",
                  "operator": {
                    "type": "string",
                    "operation": "notEquals"
                  },
                  "leftValue": "={{ $json.text }}",
                  "rightValue": "undefined "
                }
              ]
            }
          },
          "typeVersion": 2.2
        },
        {
          "id": "f89f5698-5d3c-4771-8b0b-511b32b9fc33",
          "name": "Parse AI JSON Output",
          "type": "n8n-nodes-base.code",
          "position": [
            1024,
            0
          ],
          "parameters": {
            "jsCode": "// OpenAI output comes as string in $json.text\nconst raw = $json[\"text\"];\n\n// Parse safely\nlet parsed;\ntry {\n  parsed = JSON.parse(raw);\n} catch (e) {\n  throw new Error(\"Invalid JSON returned by OpenAI: \" + raw);\n}\n\nreturn parsed;\n"
          },
          "typeVersion": 2
        },
        {
          "id": "1174cddb-9bf5-4582-a7ba-aed412336b7f",
          "name": "Calculate Weighted Quality Score",
          "type": "n8n-nodes-base.code",
          "position": [
            1232,
            0
          ],
          "parameters": {
            "jsCode": "// Input = parsed JSON from AI\nconst data = $json;\n\n// Weights (can be adjusted or moved to Config sheet later)\nconst weights = {\n  specificity: 0.35,\n  structure: 0.15,\n  bias_free_language: 0.15,\n  actionability: 0.10,\n  depth: 0.25,\n};\n\n// ✅ Fallback for structure (AI might send structure or structure_star)\nconst structureValue = data.structure ?? data.structure_star ?? 0;\n\n// Calculate weighted score safely\nlet total = (\n  (data.specificity * weights.specificity) +\n  (structureValue * weights.structure) +\n  (data.bias_free_language * weights.bias_free_language) +\n  (data.actionability * weights.actionability) +\n  (data.depth * weights.depth)\n) / (\n  weights.specificity +\n  weights.structure +\n  weights.bias_free_language +\n  weights.actionability +\n  weights.depth\n);\n\n// Scale to 0–100\ntotal = Math.round(total * 20);\n\n// Flags\nconst flags = [];\nif ((data.specificity ?? 0) < 3 || (data.depth ?? 0) < 3) {\n  flags.push(\"low_detail\");\n}\nif ((data.bias_free_language ?? 0) < 3) {\n  flags.push(\"bias\");\n}\n\n// Format vague phrases if they exist\nlet vagueFormatted = \"\";\nif (Array.isArray(data.vague_phrases) && data.vague_phrases.length > 0) {\n  vagueFormatted = data.vague_phrases.map(p => `• ${p}`).join(\"\\n\");\n}\n\n// Return clean JSON\nreturn {\n  json: {\n    Score: total,\n    Flags: flags.join(\", \"),\n    LLM_JSON: JSON.stringify(data),\n    VaguePhrasesFormatted: vagueFormatted,   // for Slack message\n    row_number: $json.row_number,            // keep tracking the row\n    Role: $item(0).$node[\"Fetch Raw Feedback Data\"].json.Role,\n    Stage: $item(0).$node[\"Fetch Raw Feedback Data\"].json.Stage\n  }\n};\n"
          },
          "typeVersion": 2
        },
        {
          "id": "5d940fc3-8727-4dc4-9a58-133ab5180f08",
          "name": "Save Scores to Spreadsheet",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
            1600,
            -208
          ],
          "parameters": {
            "columns": {
              "value": {
                "Flags": "={{ $json.Flags }}",
                "Score": "={{ $json.Score }}",
                "LLM_JSON": "={{ $json.LLM_JSON }}",
                "row_number": "={{ $('Fetch Raw Feedback Data').item.json.row_number }}"
              },
              "schema": [
                {
                  "id": "Timestamp",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Timestamp",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Candidate_ID",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Candidate_ID",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Role",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Role",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Stage",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Stage",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Interviewer_Email",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Interviewer_Email",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Feedback_Text",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Feedback_Text",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Score",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Score",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "Flags",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "Flags",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "LLM_JSON",
                  "type": "string",
                  "display": true,
                  "required": false,
                  "displayName": "LLM_JSON",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                },
                {
                  "id": "row_number",
                  "type": "number",
                  "display": true,
                  "removed": false,
                  "readOnly": true,
                  "required": false,
                  "displayName": "row_number",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
                }
              ],
              "mappingMode": "defineBelow",
              "matchingColumns": [
                "row_number"
              ],
              "attemptToConvertTypes": false,
              "convertFieldsToString": false
            },
            "options": {},
            "operation": "update",
            "sheetName": {
              "__rl": true,
              "mode": "list",
              "value": 315277036,
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y/edit#gid=315277036",
              "cachedResultName": "Raw_Feedback"
            },
            "documentId": {
              "__rl": true,
              "mode": "list",
              "value": "1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y",
              "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1Uldk_4BxWbdZTDZxFUeohIfeBmGHHqVEl9Ogb0l6R8Y/edit?usp=drivesdk",
              "cachedResultName": "Interviewer Brief Pack "
            }
          },
          "credentials": {
            "googleSheetsOAuth2Api": {
              "id": "credential-id",
              "name": "googleSheetsOAuth2Api Credential"
            }
          },
          "typeVersion": 4.6,
          "alwaysOutputData": true
        },
        {
          "id": "40df551b-4ca7-4268-a1fe-4ebb01fd304f",
          "name": "Send Feedback Summary to Interviewer",
          "type": "n8n-nodes-base.slack",
          "position": [
            1616,
            0
          ],
          "webhookId": "ddaa7632-9e35-4bd3-82d6-572d5cae84cc",
          "parameters": {
            "text": "=:mag: *Interview Feedback Audit*\n\n*Role:* {{ $json[\"Role\"] }}\n*Stage:* {{ $json[\"Stage\"] }}\n\n:bar_chart: *Score:* {{ $json[\"Score\"] }}/100  \n:warning: *Flags:* {{ $json[\"Flags\"] || \"none\" }}\n\n{{ $json[\"VaguePhrasesFormatted\"] ? \n    (\"_We noticed vague or incomplete feedback. Examples:_\\n\" + $json[\"VaguePhrasesFormatted\"] + \n    \"\\n\\n_To improve: try being more specific and evidence-based (e.g., STAR method)._\") \n    : \n    \"_✅ Great job! Your feedback was specific, structured, and bias-free._\" \n}}\n\nKeep it up — your detailed notes help us make fairer hiring decisions 🚀\n\n_Automated with this n8n workflow_\n",
            "user": {
              "__rl": true,
              "mode": "list",
              "value": "U09HMPVD466",
              "cachedResultName": "newscctv22"
            },
            "select": "user",
            "otherOptions": {}
          },
          "credentials": {
            "slackApi": {
              "id": "credential-id",
              "name": "slackApi Credential"
            }
          },
          "typeVersion": 2.3
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        {
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                  "label": "5 tasks you can automate with the new Notion API "
                },
                {
                  "url": "https://n8n.io/blog/build-your-own-virtual-assistant-with-n8n-a-step-by-step-guide/",
                  "icon": "👦",
                  "label": "Build your own virtual assistant with n8n: A step by step guide"
                },
                {
                  "url": "https://n8n.io/blog/how-to-automatically-give-kudos-to-contributors-with-github-slack-and-n8n/",
                  "icon": "👏",
                  "label": "How to automatically give kudos to contributors with GitHub, Slack, and n8n"
                },
                {
                  "url": "https://n8n.io/blog/automations-for-activists/",
                  "icon": "✨",
                  "label": "How Common Knowledge use workflow automation for activism"
                }
              ],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.slack/"
                }
              ],
              "credentialDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/credentials/slack/"
                }
              ]
            },
            "categories": [
              "Communication",
              "HITL"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "HITL": [
                "Human in the Loop"
              ]
            }
          }
        },
        "group": "[\"output\"]",
        "defaults": {
          "name": "Slack"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Slack",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 6,
            "name": "Communication"
          },
          {
            "id": 28,
            "name": "HITL"
          }
        ]
      },
      {
        "id": 565,
        "icon": "fa:sticky-note",
        "name": "n8n-nodes-base.stickyNote",
        "codex": {
          "data": {
            "alias": [
              "Comments",
              "Notes",
              "Sticky"
            ],
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers"
              ]
            }
          }
        },
        "group": "[\"input\"]",
        "defaults": {
          "name": "Sticky Note",
          "color": "#FFD233"
        },
        "iconData": {
          "icon": "sticky-note",
          "type": "icon"
        },
        "displayName": "Sticky Note",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 834,
        "icon": "file:code.svg",
        "name": "n8n-nodes-base.code",
        "codex": {
          "data": {
            "alias": [
              "cpde",
              "Javascript",
              "JS",
              "Python",
              "Script",
              "Custom Code",
              "Function"
            ],
            "details": "The Code node allows you to execute JavaScript in your workflow.",
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.code/"
                }
              ]
            },
            "categories": [
              "Development",
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Helpers",
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Code"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Code",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 5,
            "name": "Development"
          },
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 838,
        "icon": "fa:mouse-pointer",
        "name": "n8n-nodes-base.manualTrigger",
        "codex": {
          "data": {
            "resources": {
              "generic": [],
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.manualworkflowtrigger/"
                }
              ]
            },
            "categories": [
              "Core Nodes"
            ],
            "nodeVersion": "1.0",
            "codexVersion": "1.0"
          }
        },
        "group": "[\"trigger\"]",
        "defaults": {
          "name": "When clicking ‘Execute workflow’",
          "color": "#909298"
        },
        "iconData": {
          "icon": "mouse-pointer",
          "type": "icon"
        },
        "displayName": "Manual Trigger",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 9,
            "name": "Core Nodes"
          }
        ]
      },
      {
        "id": 1123,
        "icon": "fa:link",
        "name": "@n8n/n8n-nodes-langchain.chainLlm",
        "codex": {
          "data": {
            "alias": [
              "LangChain"
            ],
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Chains",
                "Root Nodes"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Basic LLM Chain",
          "color": "#909298"
        },
        "iconData": {
          "icon": "link",
          "type": "icon"
        },
        "displayName": "Basic LLM Chain",
        "typeVersion": 2,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      },
      {
        "id": 1253,
        "icon": "file:azure.svg",
        "name": "@n8n/n8n-nodes-langchain.lmChatAzureOpenAi",
        "codex": {
          "data": {
            "resources": {
              "primaryDocumentation": [
                {
                  "url": "https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatazureopenai/"
                }
              ]
            },
            "categories": [
              "AI",
              "Langchain"
            ],
            "subcategories": {
              "AI": [
                "Language Models",
                "Root Nodes"
              ],
              "Language Models": [
                "Chat Models (Recommended)"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Azure OpenAI Chat Model"
        },
        "iconData": {
          "type": "file",
          "fileBuffer": "data:image/svg+xml;base64,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"
        },
        "displayName": "Azure OpenAI Chat Model",
        "typeVersion": 1,
        "nodeCategories": [
          {
            "id": 25,
            "name": "AI"
          },
          {
            "id": 26,
            "name": "Langchain"
          }
        ]
      }
    ],
    "categories": [
      {
        "id": 17,
        "name": "HR"
      },
      {
        "id": 49,
        "name": "AI Summarization"
      }
    ],
    "image": []
  }
}