This article provides a complete, practical walkthrough of the Manual Openai Export Triggered n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Monitoring Reddit for n8n Mentions: A Smart Workflow Using AI and Automation
   
   Meta Description:  
   Learn how to automate the discovery, filtering, verification, and categorization of Reddit posts about n8n using this custom-built n8n workflow. Enhanced with OpenAI and Reddit integration for real-time insights.
   
   Keywords:  
   n8n, Reddit automation, OpenAI workflow, Reddit API, OpenAI API, workflow automation, Reddit post classification, social listening, low-code automation, community monitoring, AI content summarization
   
   Third-Party APIs Used:
   
   1. Reddit API – for searching and retrieving Reddit posts mentioning 'n8n'
   2. OpenAI API – for classifying and summarizing Reddit post content using GPT models
   
   —
   
   Article:
   
   Harnessing Reddit Intelligence: Automating n8n Mentions with AI
   
   Keeping track of community conversations about your product can be a game-changer—especially when those discussions happen across decentralized platforms like Reddit. But manually combing through each new post is time-consuming and inefficient. That’s where automation comes in.
   
   With n8n, a powerful open-source workflow automation tool, we've built a workflow that automatically discovers, verifies, and classifies Reddit posts that may be talking about “n8n,” the tool itself. This solution not only streamlines social listening but also uses AI to intelligently summarize what people are discussing. Here's a breakdown of the workflow, what it does, and where it can go next.
   
   What This Workflow Does ⚙️
   
   This n8n workflow is designed to pull in the most relevant Reddit content about n8n, determine whether it's truly about the automation tool, and then classify and summarize it using OpenAI's GPT-based API.
   
   Step-by-step, the workflow does the following:
   
   1. ✅ Triggers Manually – The search begins when you manually initiate the workflow.
   2. 🔍 Searches Reddit – Using the Reddit node, it searches for posts containing the keyword “n8n” across all of Reddit, sorted by the newest posts.
   3. 🔎 Filters for Relevance – An IF node checks three criteria: the post must be within the last 7 days, have 5 or more upvotes, and contain non-empty post content.
   4. 🧹 Sets and Trims Data – If the post makes the cut, a Set node trims the content to the first 500 characters and stores useful metadata like upvotes, subreddit size, creation date, and URL.
   5. 🤖 Uses OpenAI to Classify – The content is passed to OpenAI, with a simple yes/no prompt to determine if the post is truly about “n8n.io”.
   6. ✅ Filters by Classification – Only responses determined as "Yes" move forward to the next step.
   7. ✍️ Summarizes Content – The trimmed post content is sent to another OpenAI node, which generates a concise one-sentence summary of the post.
   8. 🔗 Merges Metadata and Summary – A merge node combines metadata from various stages with the AI-generated content summary.
   9. 📦 Final Packaging – The SetFinal node captures the cleaned and classified data into a structured format for downstream use—like dashboards, alerts, or CRM enrichment.
   
   AI Usage in the Workflow 🤖
   
   Two key OpenAI nodes elevate the intelligence of this process:
   
   - OpenAI Classify: This takes trimmed Reddit post text and evaluates whether the content is related to n8n.io using a natural language processing model with a constrained output (“Yes” or “No”) for consistency.
   - OpenAI Summary: After classification, this node rewrites post content into a short, human-readable summary, ideal for quick insights.
   
   What We Learned 💡
   
   During development, a few key insights emerged:
   
   - Prompt design matters. The results from GPT models can vary significantly based on how the prompt is phrased. For better outputs, following OpenAI’s recommended practices for prompt engineering greatly improved performance.
   - Token limits influence accuracy. Lower token counts improved yes/no classification tasks, while moderate values made summaries more natural.
   - Better UX needed. There's a great case for updating the OpenAI node in n8n to better align with popular use cases by simplifying input fields and prompts based on OpenAI's guidelines.
   
   Known Limitations 🙅
   
   - ↪ Only first 500 characters of Reddit content are evaluated. If a post mentions “n8n” deeper in the text, it might be missed.
   - ❌ The summary generation node is currently marked as “disabled” in the backup. This may result in inconsistent summaries unless the node is enabled or replaced.
   
   Next Steps and Enhancements 🚀
   
   The current setup is already valuable, but there's huge room for expansion:
   
   - Improve OpenAI prompt templates for more fleshed-out and structured summaries.
   - Add more platforms like Twitter, Discord, or specialized forums to expand listening coverage.
   - Introduce user profiling to identify posts from users that align with your Ideal Customer Profile (ICP).
   - Build sub-workflows to modularize summarization, classification, and source tracking per channel.
   
   Conclusion 📊
   
   This workflow is a powerful example of how combining automation with AI can transform a tedious task like community monitoring into a streamlined, intelligent process. With minimal configuration and open flexibility, it not only saves time—it builds a smarter, more responsive feedback loop between your community and your product.
   
   Whether you're part of a product team, community manager, or a developer looking to track meaningful discussion across Reddit, this n8n + OpenAI workflow is a high-impact starting point for automating awareness and insight.
   
   Start listening smarter—automatically.
   
   —  
   Want to try it out or adapt it to your product? You can import the JSON-based workflow directly into n8n and customize it by adjusting keywords, prompts, or adding new data sources and filters.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.