This article provides a complete, practical walkthrough of the Telegram Splitout Automation 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:
   Automating Leaderboard Reporting for n8n Creators with AI and LLMs
   
   Meta Description:
   Discover how a powerful n8n workflow leverages OpenAI, Google Gemini, and GitHub data to automatically generate and distribute insightful leaderboard reports for top n8n creators and workflows. 
   
   Keywords:
   n8n leaderboard, n8n creators, automation, OpenAI, GPT-4o, Google Gemini, GitHub, workflow automation, AI-generated reports, community engagement, markdown reports, Google Drive integration, Telegram bot integration, email automation
   
   Third-Party APIs Used:
   - OpenAI (GPT-4o-mini language model)
   - Google Gemini (Gemini 2.0 Flash Exp language model)
   - GitHub (Static JSON data hosted on GitHub Pages)
   - Google Drive API
   - Gmail API
   - Telegram Bot API
   
   Article:
   
   —
   
   # Automating Community Leaderboard Reports for n8n Creators with AI
   
   Keeping track of top contributors and popular workflows is key to building a thriving open-source community—and n8n’s ecosystem is no exception. Whether you're a community manager, core contributor, or just a passionate creator, visibility into which users and workflows are trending can drive motivation, collaboration, and even innovation.
   
   Thanks to a creatively engineered n8n workflow, reporting on the top contributors and workflows is now fully automated—combining the power of LLMs, GitHub, and daily scheduling. Aptly titled “AI Agent for n8n Creators Leaderboard Reporting,” this workflow not only compiles data-driven reports but also formats, analyzes, and distributes them using AI. Let’s explore the magic behind the process.
   
   ---
   
   ## Overview of the Workflow
   
   This n8n automation orchestrates the following actions:
   
   1. Fetches updated creator and workflow stats from a GitHub repository.
   2. Aggregates and filters data to find top contributors and workflows.
   3. Uses OpenAI and Google Gemini LLMs to write and enhance Markdown-based reports.
   4. Automatically sends these reports via Gmail, posts them to Telegram, and saves them to Google Drive.
   
   This complete automation enables a “set-it-and-forget-it” daily leaderboard reporting system that elevates community transparency and recognition.
   
   ---
   
   ## Data Sources and Global Variables
   
   At the heart of the workflow are raw data files in JSON format, hosted in a public GitHub repository (https://github.com/teds-tech-talks/n8n-community-leaderboard). They include:
   
   - creators.json: Contains data on user statistics (e.g., username, bio, total insertions, etc.).
   - workflows.json: Includes metadata about each public workflow contributed to the n8n community.
   
   Global variables define the report date, file paths, and filenames to ensure modularity and maintainability.
   
   ---
   
   ## Data Processing
   
   Once the data is retrieved, both creators and workflows are parsed and split for sorting. The workflow ranks creators by total weekly insertions and selects the top 10. For workflows, it selects the top 50 based on weekly insertions.
   
   The data is then enriched via merging: workflows are paired with their respective creators using a common key (`username`). This enriched dataset lays the foundation for deeper analysis in subsequent steps.
   
   ---
   
   ## AI-Generated Reporting
   
   This is where the workflow truly shines.
   
   A LangChain agent node powered by OpenAI’s GPT-4o-mini is tasked with analyzing the enriched data and crafting a comprehensive Markdown report. The report includes:
   
   - A detailed summary of all contributor workflows.
   - A Markdown table breaking down top workflows, visits, insertions, and appeal.
   - Analytical insights about community engagement.
   - Additional context on users' broader impact.
   
   Once generated, the Markdown content is converted to HTML for better formatting in email clients and is sent through Gmail to a predefined recipient.
   
   ---
   
   ## Highlighting the Top 10 Workflows
   
   Separately, a focused summary featuring only the top 10 workflows (hyperlinked and formatted) is created using Google Gemini's high-speed language model (Gemini 2.0 Flash Exp). This mini-report is then shared via:
   
   - Email (Gmail API)
   - Telegram (Telegram Bot API)
   
   This dual-distribution strategy ensures both detailed and quick-glance formats are available, catering to different audiences.
   
   ---
   
   ## Optional Local & Cloud Storage
   
   In addition to email and chat delivery, the reports are saved both:
   
   - Locally, in Markdown format, on a file system.
   - In Google Drive, providing access from anywhere.
   
   This ensures redundancy in distribution and easy archiving for historical reference.
   
   ---
   
   ## Automation & Scheduling
   
   Using the built-in Schedule Trigger node, automation is set to run daily at a specific hour (e.g., 10 PM). Alternatively, the execution can be triggered manually or via another workflow.
   
   ---
   
   ## Why This Workflow Matters
   
   This workflow provides a comprehensive overview of what makes an n8n community successful—its people and their ingenuity. By surfacing valuable community insights with minimal effort, users are empowered to:
   
   - Recognize contributors regularly.
   - Stay up-to-date on trending workflows.
   - Reduce manual reporting effort significantly.
   
   ---
   
   ## Conclusion
   
   This "AI Agent for n8n Creators Leaderboard Reporting" exemplifies what’s possible when LLMs meet automation. It integrates multiple platforms seamlessly—GitHub for data, OpenAI/Google Gemini for analysis, and Google Drive/Gmail/Telegram for distribution.
   
   Whether managing a small team or a large open-source community, this workflow equips you with the tools to celebrate your contributors and fuel innovation.
   
   —
   
   For anyone looking to implement or adapt the workflow, the source code and more details are available at:  
   ▶️ GitHub: https://github.com/teds-tech-talks/n8n-community-leaderboard  
   ▶️ Live Leaderboard: https://teds-tech-talks.github.io/n8n-community-leaderboard/
   
   Empower your community. Automate your insights. Recognize your creators.
   
   —
   
   Generated by AI Assistant for Community Automation Insights™

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.