{ "workflow": { "id": 10326, "name": "Generate QA test cases from Figma designs to Google Sheets using GPT-4o-mini", "views": 804, "recentViews": 2, "totalViews": 804, "createdAt": "2025-10-30T11:09:05.605Z", "description": "## Description\nTransform Figma design files into detailed QA test cases with AI-driven analysis and structured export to Google Sheets. This workflow helps QA and product teams streamline design validation, test coverage, and documentation β€” all without manual effort. πŸŽ¨πŸ€–πŸ“‹\n\n## What This Template Does\n- Step 1: Trigger manually and input your Figma file ID. 🎯\n- Step 2: Fetches the full Figma design data (layers, frames, components) via API. 🧩\n- Step 3: Sends structured design JSON to GPT-4o-mini for intelligent test case generation. 🧠\n- Step 4: AI analyzes UI components, user flows, and accessibility aspects to generate 5–10 test cases. βœ…\n- Step 5: Parses and formats results into a clean structure.\n- Step 6: Exports test cases directly to Google Sheets for QA tracking and reporting. πŸ“Š\n\n## Key Benefits\nβœ… Saves 2–3 hours per design by automating test case creation\n βœ… Ensures consistent, comprehensive QA documentation\n βœ… Uses AI to detect UX, accessibility, and functional coverage gaps\n βœ… Centralizes output in Google Sheets for easy collaboration\n\n## Features\n- Figma API integration for design parsing\n- GPT-4o-mini model for structured test generation\n- Automated Google Sheets export\n- Dynamic file ID and output schema mapping\n- Built-in error handling for large design files\n\n## Requirements\n- Figma Personal Access Token\n- OpenAI API key (GPT-4o-mini)\n- Google Sheets OAuth2 credentials\n- Target Audience\n- QA and Test Automation Engineers\n- Product & Design Teams\n- Startups and Agencies validating Figma prototypes\n\n## Setup Instructions\n- Connect your Figma token as HTTP Header Auth (X-Figma-Token).\n- Add your OpenAI API key in n8n credentials (model: gpt-4o-mini).\n- Configure Google Sheets OAuth2 and select your sheet.\n- Input Figma file ID from the design URL.\n- Run once manually, verify output, then enable for regular use.\n", "workflow": { "id": "gILrUPCbGHiFohxP", "meta": { "instanceId": "8443f10082278c46aa5cf3acf8ff0f70061a2c58bce76efac814b16290845177", "templateCredsSetupCompleted": true }, "name": "Generate QA Test Cases from Figma Designs to Google Sheets using GPT-4", "tags": [], "nodes": [ { "id": "dc0b7549-a744-4aa6-9d81-6570eae6acdb", "name": "Workflow Overview", "type": "n8n-nodes-base.stickyNote", "position": [ -1616, -320 ], "parameters": { "color": 4, "width": 400, "height": 540, "content": "## 🎨 Figma to Test Cases Generator\n\nThis workflow automates QA test case generation from Figma designs using AI.\n\n**What it does:**\n- Fetches Figma file data via API\n- Analyzes UI elements and design structure\n- Generates 5-10 comprehensive test cases using OpenAI\n- Exports test cases to Google Sheets\n\n**Use Case:**\n- QA teams needing automated test case generation\n- Product teams documenting user flows\n- Design handoff with test coverage\n\n**Requirements:**\n- Figma Personal Access Token\n- OpenAI API key (gpt-4o-mini)\n- Google Sheets OAuth2 connection\n\n**Time Saved:** ~2-3 hours per design review" }, "typeVersion": 1 }, { "id": "ef9db14b-34a0-497f-82c4-e0eb0d0fc498", "name": "Setup Guide", "type": "n8n-nodes-base.stickyNote", "position": [ -1200, -560 ], "parameters": { "color": 2, "width": 360, "height": 500, "content": "## βš™οΈ Setup Instructions\n\n**Step 1: Get Figma Token**\n- Go to Figma β†’ Settings β†’ Personal Access Tokens\n- Create new token with read access\n- Save in n8n Credentials (Header Auth)\n- Header name: `X-Figma-Token`\n\n**Step 2: Configure OpenAI**\n- Add OpenAI API key in Credentials\n- Model: gpt-4o-mini (cost-effective)\n- Est. cost: $0.02-0.05 per run\n\n**Step 3: Connect Google Sheets**\n- Create sheet with columns: `title`, `steps`\n- Authorize Google Sheets OAuth2\n- Share sheet with service account\n\n**Step 4: Input Figma File ID**\n- Get file ID from Figma URL\n- Format: `figma.com/file/{FILE_ID}/...`\n- Pass as input to workflow" }, "typeVersion": 1 }, { "id": "39541f14-cfd3-4c11-89b9-8e6aedc363fc", "name": "Figma API Notes", "type": "n8n-nodes-base.stickyNote", "position": [ -816, -480 ], "parameters": { "color": 2, "width": 300, "height": 428, "content": "## πŸ“Œ Figma API Configuration\n\n**What it fetches:**\n- Complete file structure\n- Canvas and frame data\n- Component properties\n- Text and layer info\n\n**API Parameters:**\n- `depth=1`: Single level traversal\n- `geometry=paths`: Include vector data\n\n**Important:**\n- Replace file ID with dynamic input\n- Use: `={{$json.figmaFileId}}`\n- Timeout: 30s for large files\n- Rate limit: 500 requests/min" }, "typeVersion": 1 }, { "id": "b24caffc-87cf-458e-aecb-bf00ca9309be", "name": "AI Processing Details", "type": "n8n-nodes-base.stickyNote", "position": [ -464, -448 ], "parameters": { "color": 2, "width": 280, "height": 368, "content": "## πŸ€– AI Test Generation\n\n**Analysis Includes:**\n- UI elements and interactions\n- User flow identification\n- Edge case scenarios\n- Accessibility checks (WCAG 2.1)\n- Responsive design validation\n\n**Output Format:**\nStructured JSON with test cases\n\n**Temperature:** 0.7 for creative variety\n\n**Token Usage:** ~2000-4000 per run" }, "typeVersion": 1 }, { "id": "be300909-97ca-4d0c-b7f5-077cddc16f8f", "name": "Code Logic Details", "type": "n8n-nodes-base.stickyNote", "position": [ -144, 96 ], "parameters": { "color": 2, "width": 280, "height": 260, "content": "## πŸ“Š Data Extraction\n\n**Processes AI output:**\n- Extracts test_cases array\n- Maps to Google Sheets format\n- Handles multiple test cases\n\n**Output fields:**\n- title: Test case name\n- steps: Step-by-step instructions\n\n**Error handling:**\nReturns empty array if parsing fails" }, "typeVersion": 1 }, { "id": "8aee5f1a-9b28-4951-a8c1-3438119266e9", "name": "Sheets Configuration", "type": "n8n-nodes-base.stickyNote", "position": [ 80, -560 ], "parameters": { "color": 2, "width": 300, "height": 476, "content": "## πŸ“ Google Sheets Export\n\n**Configuration:**\n- Operation: Append (adds new rows)\n- Auto-map columns enabled\n- Columns: `title`, `steps`\n\n**Sheet Structure:**\n```\n| title | steps |\n|--------------------|-----------------------|\n| Test login flow | Step 1: Click... |\n| Validate form | Step 1: Enter... |\n```\n\n**Before sharing:**\n- Remove document ID\n- Use dynamic sheet reference\n- Clear cached result data" }, "typeVersion": 1 }, { "id": "f2dee891-a0a2-4426-9f3e-b818a11b1e40", "name": "Manual Start", "type": "n8n-nodes-base.manualTrigger", "position": [ -960, -48 ], "parameters": {}, "typeVersion": 1 }, { "id": "a5cb1f68-d567-46f3-8aea-b462cede73c9", "name": "Fetch Figma Design Data", "type": "n8n-nodes-base.httpRequest", "position": [ -736, -48 ], "parameters": { "url": "=https://api.figma.com/v1/files/{{ $json.figmaFileId }}", "options": { "timeout": 30000, "response": { "response": { "neverError": true, "responseFormat": "json" } } }, "sendQuery": true, "authentication": "genericCredentialType", "genericAuthType": "httpHeaderAuth", "queryParameters": { "parameters": [ { "name": "depth", "value": "1" }, { "name": "geometry", "value": "paths" } ] } }, "credentials": { "httpHeaderAuth": { "id": "credential-id", "name": "httpHeaderAuth Credential" } }, "typeVersion": 4.2 }, { "id": "96587a6a-4e70-4c6d-a9a8-a1da7e87e7a4", "name": "OpenAI GPT-4o-mini", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ -512, 192 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini", "cachedResultName": "gpt-4o-mini" }, "options": { "maxTokens": 4000, "temperature": 0.7 } }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.2 }, { "id": "1b3d7d55-f24f-4d95-a098-7128696e7e87", "name": "Parse and Format Test Cases", "type": "n8n-nodes-base.code", "position": [ -48, -48 ], "parameters": { "jsCode": "// Extract test cases from AI agent output\nconst aiOutput = $json.output;\n\n// Safely extract test cases array\nconst testCases = aiOutput?.test_cases || [];\n\n// Validate and map to Google Sheets format\nif (!Array.isArray(testCases) || testCases.length === 0) {\n console.log('No test cases generated');\n return [];\n}\n\n// Transform to structured output\nreturn testCases.map(tc => ({\n json: {\n title: tc.title || 'Untitled Test Case',\n steps: tc.steps || 'No steps provided'\n }\n}));" }, "typeVersion": 2 }, { "id": "1efaa8c3-a934-4702-9783-7da965178a27", "name": "Export to Google Sheets", "type": "n8n-nodes-base.googleSheets", "position": [ 176, -48 ], "parameters": { "columns": { "value": {}, "schema": [ { "id": "title", "type": "string", "display": true, "removed": false, "required": false, "displayName": "title", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "steps", "type": "string", "display": true, "removed": false, "required": false, "displayName": "steps", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "autoMapInputData", "matchingColumns": [] }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "Test Cases" }, "documentId": { "__rl": true, "mode": "id", "value": "={{ $('Configure Figma File ID').item.json.googleSheetId }}" } }, "credentials": { "googleSheetsOAuth2Api": { "id": "credential-id", "name": "googleSheetsOAuth2Api Credential" } }, "typeVersion": 4.7 }, { "id": "f3e20439-3b50-414a-a67f-2dd3d0324365", "name": "JSON Output Schema", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ -256, 192 ], "parameters": { "jsonSchemaExample": "{\n \"test_cases\": [\n {\n \"title\": \"Test case title\",\n \"steps\": \"Step 1: Action\\nStep 2: Verification\\nStep 3: Expected result\"\n }\n ]\n}" }, "typeVersion": 1.3 }, { "id": "52e4bce6-4656-4658-833a-1d461fb743e5", "name": "Conversation Memory", "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow", "position": [ -384, 192 ], "parameters": { "sessionKey": "=\"figma_test_generation_\" & $('Configure Figma File ID').item.json.figmaFileId", "sessionIdType": "customKey" }, "typeVersion": 1.3 }, { "id": "0a245b2b-7d42-4dc4-9393-f07af71321f6", "name": "AI Test Case Generator", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ -464, -48 ], "parameters": { "text": "=Here is the Figma design data:\n\n{{ JSON.stringify($json, null, 2) }}\n\n**Generate 5-10 comprehensive test cases covering:**\n\n1. **UI Elements & Interactions**\n - Button states and actions\n - Form field validations\n - Navigation flows\n\n2. **User Flows**\n - Primary user journeys\n - Alternative paths\n - Error scenarios\n\n3. **Edge Cases**\n - Empty states\n - Maximum character limits\n - Invalid inputs\n\n4. **Accessibility**\n - Keyboard navigation\n - Screen reader compatibility\n - Color contrast (WCAG 2.1 AA)\n\n5. **Responsive Design**\n - Mobile viewport behavior\n - Tablet adjustments\n - Desktop optimization\n\n**Return ONLY valid JSON in this exact structure:**\n\n```json\n{\n \"test_cases\": [\n {\n \"title\": \"Descriptive test case title\",\n \"steps\": \"Step 1: Detailed action\\nStep 2: Expected behavior\\nStep 3: Verification criteria\"\n }\n ]\n}\n```\n\n**Important:** Ensure each test case has clear, actionable steps.", "options": { "systemMessage": "You are an expert QA engineer and UX analyst specializing in test case generation.\n\n**Your expertise includes:**\n- Analyzing Figma design files and extracting testable elements\n- Creating comprehensive test scenarios for web and mobile applications\n- Identifying edge cases and accessibility requirements\n- Following industry-standard QA practices (ISTQB, Agile QA)\n\n**Your task:**\nReceive Figma file data as JSON and generate detailed, actionable test cases that cover:\n- Functional requirements\n- User experience flows\n- Accessibility compliance (WCAG 2.1)\n- Cross-browser/device compatibility\n- Edge cases and error handling\n\n**Output requirements:**\n- Return ONLY valid JSON matching the provided schema\n- Each test case must have a clear title and numbered steps\n- Steps should be specific, measurable, and executable\n- Include expected results in each step\n- Prioritize critical user paths first" }, "promptType": "define", "hasOutputParser": true }, "typeVersion": 2.1 } ], "active": false, "pinData": {}, "settings": { "executionOrder": "v1" }, "versionId": "00a00b80-93a1-44c8-be7b-3cd1f78686fb", "connections": { "Manual Start": { "main": [ [ { "node": "Fetch Figma Design Data", "type": "main", "index": 0 } ] ] }, "JSON Output Schema": { "ai_outputParser": [ [ { "node": "AI Test Case Generator", "type": "ai_outputParser", "index": 0 } ] ] }, "OpenAI GPT-4o-mini": { "ai_languageModel": [ [ { "node": "AI Test Case Generator", "type": "ai_languageModel", "index": 0 } ] ] }, "Conversation Memory": { "ai_memory": [ [ { "node": "AI Test Case Generator", "type": "ai_memory", "index": 0 } ] ] }, "AI Test Case Generator": { "main": [ [ { "node": "Parse and Format Test Cases", "type": "main", "index": 0 } ] ] }, "Fetch Figma Design Data": { "main": [ [ { "node": "AI Test Case Generator", "type": "main", "index": 0 } ] ] }, "Parse and Format Test 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