This article provides a complete, practical walkthrough of the Code Schedule Automate Scheduled 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:  
   Automated PR Intel: How n8n and Reddit Power Weekly Digital Story Mining for PR Teams
   
   Meta Description:  
   Discover how an advanced n8n workflow uses Reddit sentiment analysis, Jina AI content extraction, and Anthropic’s Claude models to deliver automatically generated PR story ideas—curated, analyzed, and delivered weekly to your team.
   
   Keywords:  
   n8n workflow, Reddit API, PR automation, sentiment analysis, Anthropic Claude, Jina AI, digital PR, automated content analysis, Google Drive integration, Mattermost alerts, content extraction
   
   Third-Party APIs Used:
   
   1. Reddit API  
      — Used for searching posts and retrieving comments from Reddit based on trending topics.
   
   2. Jina AI API  
      — Employed to extract clean content from shared news URLs using its readerlm-v2 model.
   
   3. Anthropic Claude (via LangChain integration)  
      — Claude-3 Sonnet model is used for multi-stage natural language processing tasks including:
      - Reddit sentiment analysis
      - News article evaluation
      - PR story generation
   
   4. Google Drive API  
      — Automates report storage and sharing with predefined permissions.
   
   5. Mattermost Webhook API  
      — Used to notify team members in the “digital-pr” channel about new weekly reports.
   
   —
   
   Article:
   
   In today's attention economy, Public Relations (PR) professionals are fighting an uphill battle. With real-time discourse fragmenting across platforms, identifying emerging stories before they go mainstream often relies on a mix of luck, good timing, and relentless manual scanning. But what if PR discovery and analysis could be automated—delivering sentiment-analyzed, insight-packed story suggestions every week?
   
   That’s exactly the problem this powerful n8n workflow aimed to solve. Let’s unpack how it works.
   
   A Fully Automated Content Intelligence Engine
   
   At its core, this workflow builds an intelligent system to mine Reddit for the most promising story ideas aligned with user-defined topics. Every Monday at 6:00 AM, the workflow executes, following this high-level process:
   
   1. Define Focus Topics  
   The workflow starts by allowing PR teams to define a custom list of story-relevant topics such as “Donald Trump” or “Politics.” These are input into n8n manually and can be changed at any time.
   
   2. Discover Reddit Content  
   Using the Reddit API, the workflow searches for “hot” posts matching each topic. Only high-engagement posts are retained—those with:
   - More than 100 upvotes
   - “Link” post type
   - External links that exclude Reddit or bsky.app URLs
   
   3. Clean, Deduplicate & Format  
   From this curated list, duplicate links are removed, preserving only the post with the highest upvotes for each unique URL. The result is a clean, high-quality list of Reddit posts linking to trending stories.
   
   4. Analyze Reddit Comments  
   For each high-performing Reddit post, the system pulls associated comments and uses an intelligent comment parser to:
   - Clean and flatten nested comments
   - Remove deleted or irrelevant entries
   - Select the top 30 comments based on upvotes
   - Preserve comment threading for contextual analysis
   
   The comments are also formatted in Markdown, maintaining hierarchy for easy readability.
   
   5. Claude-Powered Sentiment & Trend Analysis  
   The impressive part? Claude comes in not once, but three times:
   - First, it analyzes Reddit discussions across engagement, sentiment, emotional depth, and ownership of narrative.
   - Then, it gets paired with the original news URL content (extracted using Jina AI) to conduct a full PR analysis of the news article itself.
   - Finally, Claude generates fully fleshed-out PR story opportunities based on the convergence of public discourse, sentiment, and gaps in current media coverage.
   
   6. Reporting & Sharing  
   Post-analysis, the system creates a final report per story, combining:
   - Reddit link and metrics
   - A detailed “new_stories_report” section (including headlines and media strategies)
   - Source content analysis
   - Public comment trend summaries
   
   These reports are turned into .txt files with meaningful names based on the article headline. All reports get compressed into a ZIP file and automatically uploaded to a Google Drive folder. The system also shares a public download link through a Mattermost webhook post, notifying the PR team in real time.
   
   Why This Matters for PR Teams
   
   The brilliance of this workflow lies not just in automation, but in intelligence:
   
   - Always-On Trends: With its schedule trigger, teams receive story updates regularly without lifting a finger.
   
   - Real Engagement Metrics: By analyzing crowd-sourced comments, PR teams get insight into what the public thinks—not just what journalists write.
   
   - Insight-backed Headlines: Claude doesn’t just summarize. It creatively identifies unique PR hooks, complete with audience, risk, and development suggestions.
   
   - Seamless Collaboration: With Mattermost and Google Drive integrations, discovery results aren’t siloed—they’re immediately shared with your team.
   
   Ultimate Outcome: A Streamlined PR Pipeline
   
   From top-of-funnel story identification to end-of-funnel report delivery, this n8n-powered system acts as a full-fledged PR story engine, enabling:
   - Smarter brainstorming meetings
   - Quicker decision-making on timely PR pushes
   - Data-backed strategy presentations to clients
   
   In a world where news breaks and dies in cycles of minutes, having a proactive digital tool like this redefines your competitive edge.
   
   Conclusion
   
   This workflow showcases just how far automation can go—not merely streamlining tasks, but conducting actual journalism-style analysis with AI support. By weaving together Reddit discussions, AI-driven sentiment parsing, article summarization, and professional-grade media planning, this n8n workflow turns Reddit into a PR goldmine.
   
   For anyone in digital PR, media monitoring, or trend forecasting, it’s an inspiring blueprint for blending intelligence automation with real-world storytelling strategy.
   
   —  
   Ready to bring this to life? With a few tweaks to credentials and topics, your team can put this exact system into production within hours.

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.