{
  "name": "LinkedIn Content Automation (RSS + Gemini)",
  "nodes": [
    {
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "cronExpression",
              "expression": "0 8 * * *"
            }
          ]
        }
      },
      "id": "schedule-trigger",
      "name": "Schedule Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "typeVersion": 1.2,
      "position": [
        240,
        300
      ]
    },
    {
      "parameters": {
        "url": "https://feeds.feedburner.com/TechCrunch/",
        "options": {}
      },
      "id": "rss-feed-1",
      "name": "RSS Feed - TechCrunch",
      "type": "n8n-nodes-base.rssFeedRead",
      "typeVersion": 1,
      "position": [
        460,
        200
      ]
    },
    {
      "parameters": {
        "url": "https://www.theverge.com/rss/index.xml",
        "options": {}
      },
      "id": "rss-feed-2",
      "name": "RSS Feed - The Verge",
      "type": "n8n-nodes-base.rssFeedRead",
      "typeVersion": 1,
      "position": [
        460,
        400
      ]
    },
    {
      "parameters": {},
      "id": "merge-feeds",
      "name": "Merge RSS Feeds",
      "type": "n8n-nodes-base.merge",
      "typeVersion": 2.1,
      "position": [
        680,
        300
      ]
    },
    {
      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "leftValue": "",
            "typeValidation": "strict"
          },
          "conditions": [
            {
              "id": "check-date",
              "leftValue": "={{ $json.pubDate }}",
              "rightValue": "={{ $now.minus({hours: 24}).toISO() }}",
              "operator": {
                "type": "dateTime",
                "operation": "after",
                "singleValue": true
              }
            }
          ],
          "combinator": "and"
        },
        "options": {}
      },
      "id": "filter-recent",
      "name": "Filter Last 24hrs",
      "type": "n8n-nodes-base.filter",
      "typeVersion": 2,
      "position": [
        900,
        300
      ]
    },
    {
      "parameters": {
        "assignments": {
          "assignments": [
            {
              "id": "title",
              "name": "article_title",
              "value": "={{ $json.title }}",
              "type": "string"
            },
            {
              "id": "link",
              "name": "article_link",
              "value": "={{ $json.link }}",
              "type": "string"
            },
            {
              "id": "description",
              "name": "article_description",
              "value": "={{ $json.description }}",
              "type": "string"
            },
            {
              "id": "pubdate",
              "name": "published_date",
              "value": "={{ $json.pubDate }}",
              "type": "string"
            },
            {
              "id": "source",
              "name": "source",
              "value": "={{ $json.meta?.title || 'RSS Feed' }}",
              "type": "string"
            }
          ]
        },
        "options": {}
      },
      "id": "extract-article-data",
      "name": "Extract Article Data",
      "type": "n8n-nodes-base.set",
      "typeVersion": 3.4,
      "position": [
        1120,
        300
      ]
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent",
        "authentication": "genericCredentialType",
        "genericAuthType": "queryAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={\n  \"contents\": [{\n    \"parts\": [{\n      \"text\": \"You are a LinkedIn content strategist. Analyze this article and determine if it's suitable for LinkedIn content for a B2B AI automation agency.\\n\\nArticle Title: {{ $json.article_title }}\\nDescription: {{ $json.article_description }}\\nSource: {{ $json.source }}\\n\\nEvaluate:\\n1. RELEVANCE SCORE (0-100): How relevant is this to B2B decision makers, technology, AI, automation, or business innovation?\\n2. ENGAGEMENT POTENTIAL (0-100): How likely is this to generate likes, comments, and shares on LinkedIn?\\n3. KEY TAKEAWAY: What's the main insight or lesson from this article?\\n4. TARGET AUDIENCE: Who should read this? (e.g., CEOs, Marketing Directors, Tech Leaders)\\n5. CONTENT ANGLE: What perspective should we take when posting about this?\\n\\nOnly recommend articles with BOTH scores above 60.\\n\\nFormat response as JSON with keys: relevance_score, engagement_potential, key_takeaway, target_audience, content_angle, recommended (boolean)\"\n    }]\n  }]\n}",
        "options": {}
      },
      "id": "gemini-analyze",
      "name": "Gemini - Analyze Article",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        1340,
        300
      ]
    },
    {
      "parameters": {
        "jsCode": "// Parse AI response\nconst aiResponse = $input.item.json.candidates[0].content.parts[0].text;\n\nlet analysisData;\ntry {\n  const cleanedResponse = aiResponse.replace(/```json\\n?|```\\n?/g, '').trim();\n  analysisData = JSON.parse(cleanedResponse);\n} catch (error) {\n  // Fallback if parsing fails\n  analysisData = {\n    relevance_score: 0,\n    engagement_potential: 0,\n    key_takeaway: \"Unable to analyze\",\n    target_audience: \"General\",\n    content_angle: \"Informative\",\n    recommended: false\n  };\n}\n\n// Get article data\nconst articleData = $('Extract Article Data').item.json;\n\n// Combine everything\nreturn {\n  ...articleData,\n  relevance_score: analysisData.relevance_score,\n  engagement_potential: analysisData.engagement_potential,\n  key_takeaway: analysisData.key_takeaway,\n  target_audience: analysisData.target_audience,\n  content_angle: analysisData.content_angle,\n  recommended: analysisData.recommended\n};"
      },
      "id": "parse-analysis",
      "name": "Parse Analysis",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        1560,
        300
      ]
    },
    {
      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "leftValue": "",
            "typeValidation": "strict"
          },
          "conditions": [
            {
              "id": "check-recommended",
              "leftValue": "={{ $json.recommended }}",
              "rightValue": true,
              "operator": {
                "type": "boolean",
                "operation": "true",
                "singleValue": true
              }
            },
            {
              "id": "check-relevance",
              "leftValue": "={{ $json.relevance_score }}",
              "rightValue": 60,
              "operator": {
                "type": "number",
                "operation": "gte"
              }
            }
          ],
          "combinator": "and"
        },
        "options": {}
      },
      "id": "filter-recommended",
      "name": "Filter Recommended Only",
      "type": "n8n-nodes-base.filter",
      "typeVersion": 2,
      "position": [
        1780,
        300
      ]
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent",
        "authentication": "genericCredentialType",
        "genericAuthType": "queryAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={\n  \"contents\": [{\n    \"parts\": [{\n      \"text\": \"Create an engaging LinkedIn post based on this article. The post is for a B2B AI automation agency.\\n\\nArticle Title: {{ $json.article_title }}\\nKey Takeaway: {{ $json.key_takeaway }}\\nTarget Audience: {{ $json.target_audience }}\\nContent Angle: {{ $json.content_angle }}\\nArticle Link: {{ $json.article_link }}\\n\\nRequirements:\\n- Hook: Start with an attention-grabbing first line\\n- Length: 150-200 words (LinkedIn optimal)\\n- Value: Share insights, not just news\\n- Tone: Professional but conversational, thought-provoking\\n- Structure: Short paragraphs (2-3 lines max)\\n- CTA: End with a question or call-to-action to drive engagement\\n- Include 3-5 relevant hashtags\\n- Credit the source naturally\\n- DO NOT use emojis\\n\\nReturn ONLY the post text, ready to copy-paste.\"\n    }]\n  }]\n}",
        "options": {}
      },
      "id": "gemini-create-post",
      "name": "Gemini - Create LinkedIn Post",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        2000,
        300
      ]
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash-exp:generateContent",
        "authentication": "genericCredentialType",
        "genericAuthType": "queryAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={\n  \"contents\": [{\n    \"parts\": [{\n      \"text\": \"Based on this article and LinkedIn post, suggest the optimal posting time and date.\\n\\nArticle: {{ $json.article_title }}\\nTarget Audience: {{ $json.target_audience }}\\nEngagement Potential: {{ $json.engagement_potential }}/100\\n\\nConsider:\\n- Current date/time: {{ $now.toFormat('yyyy-MM-dd HH:mm') }}\\n- LinkedIn best practices (Tue-Thu, 8-10am or 12-1pm work hours)\\n- Content freshness (post within 24-48 hours of article)\\n- Audience availability\\n\\nProvide:\\n1. SUGGESTED_DATE: Date in format YYYY-MM-DD\\n2. SUGGESTED_TIME: Time in format HH:MM (24-hour)\\n3. REASONING: Brief explanation (one sentence)\\n\\nFormat as JSON with keys: suggested_date, suggested_time, reasoning\"\n    }]\n  }]\n}",
        "options": {}
      },
      "id": "gemini-schedule",
      "name": "Gemini - Suggest Schedule",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [
        2000,
        480
      ]
    },
    {
      "parameters": {
        "jsCode": "// Get the post content\nconst postResponse = $('Gemini - Create LinkedIn Post').first().json.candidates[0].content.parts[0].text;\n\n// Get the schedule suggestion\nconst scheduleResponse = $input.item.json.candidates[0].content.parts[0].text;\n\nlet scheduleData;\ntry {\n  const cleanedSchedule = scheduleResponse.replace(/```json\\n?|```\\n?/g, '').trim();\n  scheduleData = JSON.parse(cleanedSchedule);\n} catch (error) {\n  // Default to tomorrow at 9am if parsing fails\n  const tomorrow = $now.plus({days: 1});\n  scheduleData = {\n    suggested_date: tomorrow.toFormat('yyyy-MM-dd'),\n    suggested_time: '09:00',\n    reasoning: 'Default schedule'\n  };\n}\n\n// Get all article data\nconst articleData = $('Filter Recommended Only').first().json;\n\n// Generate post ID for tracking\nconst postId = `POST_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;\n\n// Create final output\nreturn {\n  post_id: postId,\n  status: 'Draft',\n  scheduled_date: scheduleData.suggested_date,\n  scheduled_time: scheduleData.suggested_time,\n  scheduling_reason: scheduleData.reasoning,\n  post_content: postResponse.trim(),\n  article_title: articleData.article_title,\n  article_link: articleData.article_link,\n  source: articleData.source,\n  relevance_score: articleData.relevance_score,\n  engagement_potential: articleData.engagement_potential,\n  target_audience: articleData.target_audience,\n  key_takeaway: articleData.key_takeaway,\n  created_at: $now.toISO(),\n  posted_at: '',\n  performance_likes: '',\n  performance_comments: '',\n  performance_shares: '',\n  notes: ''\n};"
      },
      "id": "prepare-calendar-entry",
      "name": "Prepare Calendar Entry",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        2220,
        300
      ]
    },
    {
      "parameters": {
        "operation": "append",
        "documentId": {
          "__rl": true,
          "value": "REPLACE_WITH_RESOURCE",
          "mode": "list"
        },
        "sheetName": {
          "__rl": true,
          "value": "REPLACE_WITH_RESOURCE",
          "mode": "list"
        },
        "columns": {
          "mappingMode": "autoMapInputData",
          "value": {},
          "matchingColumns": [],
          "schema": [
            {
              "id": "post_id",
              "displayName": "Post ID",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "status",
              "displayName": "Status",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "scheduled_date",
              "displayName": "Scheduled Date",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "scheduled_time",
              "displayName": "Scheduled Time",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "post_content",
              "displayName": "Post Content",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "article_title",
              "displayName": "Article Title",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "article_link",
              "displayName": "Article Link",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "source",
              "displayName": "Source",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "relevance_score",
              "displayName": "Relevance Score",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "number",
              "canBeUsedToMatch": true
            },
            {
              "id": "engagement_potential",
              "displayName": "Engagement Potential",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "number",
              "canBeUsedToMatch": true
            },
            {
              "id": "target_audience",
              "displayName": "Target Audience",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "key_takeaway",
              "displayName": "Key Takeaway",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "created_at",
              "displayName": "Created At",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "posted_at",
              "displayName": "Posted At",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "performance_likes",
              "displayName": "Likes",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "performance_comments",
              "displayName": "Comments",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "performance_shares",
              "displayName": "Shares",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "notes",
              "displayName": "Notes",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            },
            {
              "id": "scheduling_reason",
              "displayName": "Scheduling Reason",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "canBeUsedToMatch": true
            }
          ]
        },
        "options": {}
      },
      "id": "google-sheets-calendar",
      "name": "Add to Content Calendar",
      "type": "n8n-nodes-base.googleSheets",
      "typeVersion": 4.5,
      "position": [
        2440,
        300
      ]
    },
    {
      "id": "83f0029f-a849-5216-9ae6-dc4e4150502d",
      "name": "Publication · Overview and setup",
      "type": "n8n-nodes-base.stickyNote",
      "typeVersion": 1,
      "position": [
        -800,
        0
      ],
      "parameters": {
        "content": "# LinkedIn Content Automation (RSS + Gemini)\n\n## Purpose and structure\nThis folder contains the **LinkedIn Content Automation (RSS + Gemini)** workflow. Its executable nodes use `code`, `filter`, `googleSheets`, `httpRequest`, `merge`, `rssFeedRead`, `scheduleTrigger`, `set`. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.\n\n## Setup\nImport inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.\n\n## Entry points\nSchedule Trigger\n\n## Verification\nSanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.\n\n## Attribution\nhttps://github.com/skadaai/awesome-n8n-templates/blob/4eabc190bf6fac4073e3e1dcaabf0f72897770eb/li-post.json\nMIT; preserve source notices.",
        "width": 700,
        "height": 800,
        "color": 1
      }
    }
  ],
  "connections": {
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "RSS Feed - TechCrunch",
            "type": "main",
            "index": 0
          },
          {
            "node": "RSS Feed - The Verge",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "RSS Feed - TechCrunch": {
      "main": [
        [
          {
            "node": "Merge RSS Feeds",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "RSS Feed - The Verge": {
      "main": [
        [
          {
            "node": "Merge RSS Feeds",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Merge RSS Feeds": {
      "main": [
        [
          {
            "node": "Filter Last 24hrs",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Filter Last 24hrs": {
      "main": [
        [
          {
            "node": "Extract Article Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Extract Article Data": {
      "main": [
        [
          {
            "node": "Gemini - Analyze Article",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Gemini - Analyze Article": {
      "main": [
        [
          {
            "node": "Parse Analysis",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Parse Analysis": {
      "main": [
        [
          {
            "node": "Filter Recommended Only",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Filter Recommended Only": {
      "main": [
        [
          {
            "node": "Gemini - Create LinkedIn Post",
            "type": "main",
            "index": 0
          },
          {
            "node": "Gemini - Suggest Schedule",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Gemini - Create LinkedIn Post": {
      "main": [
        [
          {
            "node": "Prepare Calendar Entry",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Gemini - Suggest Schedule": {
      "main": [
        [
          {
            "node": "Prepare Calendar Entry",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Prepare Calendar Entry": {
      "main": [
        [
          {
            "node": "Add to Content Calendar",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  },
  "active": false
}