Automated Learning Resource Recommendation Generator from Hacker News - n8n Workflow

• Lifelong Learners: Individuals constantly looking for high-quality, community-vetted resources.


• Content Curators: Those who need fast summaries of community sentiment and top recommendations.


• n8n Users: Users seeking advanced n8n templates integrating scraping, LLMs, and email actions.


• Automation Enthusiasts: Anyone wanting a practical example of a complex, multi-step n8n node chain.

Finding the best resources to learn a new skill can be overwhelming, often requiring hours of digging through forums. This specialized n8n workflow solves this by harnessing the collective knowledge of Hacker News (HN). When a user submits a topic via the initial n8n trigger, the system queries HN's Ask HN section. It retrieves hundreds of related comments, aggregates them, and feeds the raw text into a powerful LLM (Google Gemini). The LLM analyzes the sentiment and content of every comment to categorize and list the absolute top recommendations. This robust n8n automation ensures you receive curated, high-quality advice directly in your inbox, demonstrating the immense power of an advanced n8n workflow.

This powerful n8n workflow starts with the GetTopicFromToLearn n8n trigger, which is an HTTP Form.

1. Trigger and Search: When the user submits the topic and email, the flow activates. The data is passed to the SearchAskHN n8n node, which queries Hacker News for relevant 'Ask HN' threads related to the learning topic.


2. Data Extraction: The resulting HN post IDs are passed to the SplitOutChildrenIDs n8n node, which isolates the comment IDs. The FindHNComments HTTP Request n8n node then iteratively fetches the full content of each comment.


3. Preparation: The CombineIntoSingleText n8n node aggregates all individual comments into one large text block, preparing the data payload for the AI. This is a crucial step in this n8n workflow.


4. AI Analysis: The aggregated text enters the Basic LLM Chain n8n node, which utilizes the connected Google Gemini Chat Model to execute a detailed prompt. This prompt mandates the LLM to identify, categorize (by type and difficulty), and summarize the top resources recommended within the comment section, responding in Markdown format. This powerful n8n node executes the core logic.


5. Delivery: The Markdown output is converted to clean HTML by the Convert2HTML n8n node. Finally, the SendEmailWithTopResources n8n node uses the user's provided email address (captured by the initial n8n trigger) to send the highly curated recommendation list, completing this robust n8n workflow.

To deploy this comprehensive n8n workflow, follow these steps:

1. Import the n8n template: Copy the provided JSON and import it directly into your n8n instance.


2. Configure Credentials:

1. Activate the Trigger: The GetTopicFromToLearn n8n trigger creates a public URL for the form. Publish the n8n workflow to start accepting user submissions.


2. Test: Submit a learning topic via the generated form URL to ensure the n8n node sequence executes correctly and you receive the resulting email, confirming the success of this n8n template.

• GetTopicFromToLearn (Form Trigger): The starting n8n trigger for the workflow. Captures the user's learning topic and email address.


• SearchAskHN (Hacker News n8n node): Queries Hacker News specifically for posts tagged 'ask_hn' using the submitted topic as the keyword. Limited to 150 results.


• SplitOutChildrenIDs (Split Out n8n node): Processes the HN story JSON to extract the IDs of all linked comments (children) into separate items for processing.


• FindHNComments (HTTP Request n8n node): Iterates over each comment ID using a dynamic URL to fetch the comment text from the HN Firebase API.


• CombineIntoSingleText (Aggregate n8n node): Merges all fetched comments into a single item with a single text field, optimizing input for the subsequent LLM chain.


• Google Gemini Chat Model (AI Language Model): Provides the language model capability, specifically using models/gemini-1.5-flash to process the prompts.


• Basic LLM Chain (Langchain n8n node): The core intelligence n8n node. It uses a lengthy, precise prompt that instructs the Gemini model to perform sentiment analysis, resource extraction, categorization (course, book, article), and difficulty assessment based on the scraped comments. This demonstrates complex usage of the n8n node features.


• Convert2HTML (Markdown n8n node): Transforms the structured Markdown output generated by the AI into HTML format, ensuring optimal display in the final email.


• SendEmailWithTopResources (Email Send n8n node): The final action. Sends the HTML-formatted recommendations to the user email captured by the initial n8n trigger, confirming the successful execution of the n8n workflow.