25 機能リクエストを収集

• •OpenAI API Key

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  "name": "25 Gather Feature Requests",
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        "text": "=Extract review text, title, date and username (if any) from the following url. Make sure to extract only those reviews that are asking for functionality for better user experiance.\n\nURL: {{ $json.URL }}",
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    },
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        "summary": "=Below are the feature requests from the users on trustpilot:\n\nTitle: {{ $json.title }}\nURL: {{ $json.url }}\nDate: {{ $json.date }}\nUsername: {{ $json.username }}\nFeature request: {{ $json.review_text }}",
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        "toolName": "scrape_as_markdown",
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        "content": "## 🧩 **Section 1: Start and Target Setup**\n\n📦 **Nodes Combined**:\n\n* `🔘 Start Manual Execution`\n* `🖊️ Edit Target Site URL`\n\n### 🔍 What Happens Here:\n\nThis section is where your workflow **begins** and gets the **input URL** of the review site.\n\n* ✅ **Manual Trigger**:\n  Allows you to run this workflow by clicking “Execute Workflow.” Great for testing new URLs.\n\n* ✍️ **Edit Field**:\n  You input the **URL of the review page**, such as:\n\n  * `https://www.g2.com/products/clickup/reviews`\n  * `https://www.trustpilot.com/review/clickup.com`\n\n### 💡 Beginner Tip:\n\nInstead of hardcoding URLs in code, this editable field makes it easy for **non-developers** to change input by just typing/pasting the review page.\n\n---\n\n"
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        "content": "## 🤖 **Section 2: Scrape and Structure User Reviews**\n\n🛠️ **Core Nodes**:\n\n* `🤖 Scrape Reviews using Agent`\n* `🌐 Bright Data MCP Scraper`\n* `🧠 OpenAI Chat Model (Optional)`\n* `🧾 Parse Structured Agent Output`\n\n### 🔍 What Happens Here:\n\nThis section uses **AI + Bright Data** to fetch review content, extract important insights, and prepare structured output.\n\n* 🌐 **Agent Node**:\n  Launches your custom scraper (via Bright Data MCP) to visit the site and collect reviews.\n\n* 🧾 **Output Parser**:\n  Cleans up the output to return just the **structured review objects** like:\n\n  ```json\n  {\n    \"title\": \"...\",\n    \"username\": \"...\",\n    \"review_text\": \"...\",\n    \"date\": \"...\"\n  }\n  ```\n\n* 🧠 **(Optional AI Model)**:\n  If used, this can:\n\n  * Classify reviews into categories (e.g., UI issue, billing issue)\n  * Summarize long reviews\n  * Extract common themes or keywords\n\n### 💡 Beginner Tip:\n\nThis is where the **heavy lifting happens** — the agent goes out and scrapes the content **so you don’t have to copy-paste reviews manually.**\n\n---\n\n"
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        "content": "## 🧾 **Section 3: Convert Reviews into Jira Tasks**\n\n🧩 **Final Nodes**:\n\n* `🧩 Format Individual Reviews` (Function Node)\n* `🗂️ Create Feature Ticket in Jira`\n\n### 🔍 What Happens Here:\n\nEach review gets **processed and pushed to Jira** as an individual ticket so your product team can track it.\n\n* 🔄 **Split Function Node**:\n  Takes the list of 5+ reviews returned by the agent and **splits them one by one** so Jira receives **a single review per ticket**.\n\n* 📋 **Jira Node**:\n  Sends the review content to **Jira Software**, creating a ticket like:\n\n  * **Summary**: `\"Feature Request: Better Dashboard Customization\"`\n  * **Description**: `\"James (Jul 24, 2024): 'It would be nice to see a simplified home screen and personalized dashboards.'\"`\n  * **Priority**: Can be assigned based on keyword frequency or sentiment.\n\n### 💡 Beginner Tip:\n\nYou’re now **automatically turning feedback into action**, saving hours of reading and logging manually into Jira.\n\n---\n\n"
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        "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
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        "content": "## 🌟 Workflow Title:\n\n# **📥 Gather & Prioritize Feature Requests into Jira (Trustpilot)**\n\n\n*“Automatically collect real user feedback and convert it into actionable Jira tasks using scraping and AI.”*\n\n---\n\n## 🧩 **Section 1: Start and Target Setup**\n\n📦 **Nodes Combined**:\n\n* `🔘 Start Manual Execution`\n* `🖊️ Edit Target Site URL`\n\n### 🔍 What Happens Here:\n\nThis section is where your workflow **begins** and gets the **input URL** of the review site.\n\n* ✅ **Manual Trigger**:\n  Allows you to run this workflow by clicking “Execute Workflow.” Great for testing new URLs.\n\n* ✍️ **Edit Field**:\n  You input the **URL of the review page**, such as:\n\n  * `https://www.g2.com/products/clickup/reviews`\n  * `https://www.trustpilot.com/review/clickup.com`\n\n### 💡 Beginner Tip:\n\nInstead of hardcoding URLs in code, this editable field makes it easy for **non-developers** to change input by just typing/pasting the review page.\n\n---\n\n## 🤖 **Section 2: Scrape and Structure User Reviews**\n\n🛠️ **Core Nodes**:\n\n* `🤖 Scrape Reviews using Agent`\n* `🌐 Bright Data MCP Scraper`\n* `🧠 OpenAI Chat Model (Optional)`\n* `🧾 Parse Structured Agent Output`\n\n### 🔍 What Happens Here:\n\nThis section uses **AI + Bright Data** to fetch review content, extract important insights, and prepare structured output.\n\n* 🌐 **Agent Node**:\n  Launches your custom scraper (via Bright Data MCP) to visit the site and collect reviews.\n\n* 🧾 **Output Parser**:\n  Cleans up the output to return just the **structured review objects** like:\n\n  ```json\n  {\n    \"title\": \"...\",\n    \"username\": \"...\",\n    \"review_text\": \"...\",\n    \"date\": \"...\"\n  }\n  ```\n\n* 🧠 **(Optional AI Model)**:\n  If used, this can:\n\n  * Classify reviews into categories (e.g., UI issue, billing issue)\n  * Summarize long reviews\n  * Extract common themes or keywords\n\n### 💡 Beginner Tip:\n\nThis is where the **heavy lifting happens** — the agent goes out and scrapes the content **so you don’t have to copy-paste reviews manually.**\n\n---\n\n## 🧾 **Section 3: Convert Reviews into Jira Tasks**\n\n🧩 **Final Nodes**:\n\n* `🧩 Format Individual Reviews` (Function Node)\n* `🗂️ Create Feature Ticket in Jira`\n\n### 🔍 What Happens Here:\n\nEach review gets **processed and pushed to Jira** as an individual ticket so your product team can track it.\n\n* 🔄 **Split Function Node**:\n  Takes the list of 5+ reviews returned by the agent and **splits them one by one** so Jira receives **a single review per ticket**.\n\n* 📋 **Jira Node**:\n  Sends the review content to **Jira Software**, creating a ticket like:\n\n  * **Summary**: `\"Feature Request: Better Dashboard Customization\"`\n  * **Description**: `\"James (Jul 24, 2024): 'It would be nice to see a simplified home screen and personalized dashboards.'\"`\n  * **Priority**: Can be assigned based on keyword frequency or sentiment.\n\n### 💡 Beginner Tip:\n\nYou’re now **automatically turning feedback into action**, saving hours of reading and logging manually into Jira.\n\n---\n\n## ✅ Why This Workflow is Powerful:\n\n| Benefit                       | Description                                                          |\n| ----------------------------- | -------------------------------------------------------------------- |\n| ⏱️ **Time-Saving**            | No need to copy/paste from reviews — everything is automated.        |\n| 🧠 **AI-Driven**              | Optional summarization and categorization using OpenAI.              |\n| 📊 **Product Prioritization** | Focus on real user pain points based on what’s actually said online. |\n| 💻 **No Code Required**       | All steps are configurable in n8n with drag-and-drop ease.           |\n\n---\n\n"
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        "content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
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