This article provides a complete, practical walkthrough of the Splitout Code Send 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 Weekly Slack Activity Reports with AI Using n8n
   
   Meta Description:  
   Learn how to automate the generation of team-wide Slack activity summaries using n8n and Google Gemini AI. This workflow fetches weekly messages, summarizes threads, and posts team reports—perfect for remote teams and project managers.
   
   Keywords:  
   n8n, Slack automation, AI summarization, Google Gemini, project management, remote teams, automated reports, team summary, Slack threads, weekly activity report
   
   Third-Party APIs Used:
   
   1. Slack API  
      - Used to fetch messages, threads, user information, and to post final reports to Slack channels.
   
   2. Google Gemini API (formerly PaLM)  
      - Used for summarizing individual Slack threads, generating user-specific weekly summaries, and composing a final team-wide report using advanced AI language models.
   
   Article:
   
   ---
   
   In the fast-paced world of remote collaboration, teams often communicate through short, fragmented Slack messages and threads. These conversations drive projects forward but can be hard to track or reference later. What if you could automate the collation and summarization of your team's Slack activity each week, delivering a motivational and actionable summary every Monday morning?
   
   Enter this powerful n8n workflow—a fully customizable template that integrates Slack with Google Gemini to produce weekly Slack activity reports. Not only does it scan through your team messages, but it also highlights wins, challenges, decisions, and welcomes or farewells. Here’s how it works and why it's a productivity booster.
   
   Step 1: Fetch Last Week’s Slack Messages  
   Every Monday at 6am, the workflow kicks into action with a Schedule Trigger. It retrieves all messages posted in a specified Slack channel—typically a main team or project channel—filtering for just the past seven days.
   
   The messages are then grouped by author, so each team member’s activity can be tracked independently. This data becomes the foundation for further analysis that dives into context and collaboration.
   
   Step 2: Capture the Full Conversation  
   Rather than taking messages at face value, the workflow digs deeper. For every top-level message (not replies), it fetches the associated thread of replies. This includes contributions from other users, forming a clear discussion narrative.
   
   Using nested subworkflows—a best practice in n8n when working with large data sets—the system simplifies message threading and ensures each reply is accurately mapped to its parent message.
   
   Step 3: Use AI to Summarize Threads  
   Once the content is collected and simplified, the workflow calls on Google Gemini’s LLM to summarize each thread. The AI identifies if the topic discussed was about a win (e.g., a product launch), a challenge (e.g., a bug or deadline), or an announcement (e.g., a team member joining or leaving).
   
   Each thread summary condenses possibly lengthy conversations into concise and context-rich synopses. This ensures that key insights aren't lost in the noise.
   
   Step 4: Create Individual Team Member Reports  
   The final summaries for each team member are aggregated and passed back to Gemini AI once again. This time, the prompt instructs the model to generate a motivating, engaging weekly report for that member, referencing all their contributions and interactions.
   
   These individual mini-reports are styled for a motivational tone—celebrating achievements, spotlighting issues, and encouraging collaboration.
   
   Step 5: Generate and Post the Team Summary  
   All individual reports are then rolled into a combined team-wide summary. This panoramic view gives everyone insight into what happened across the team last week. If certain projects saw collaboration by multiple members, the report connects the dots. If someone’s been silent, it might mention that too and encourage feedback or engagement.
   
   The final polished report is posted to your Slack channel first thing Monday morning—ready for teams to skim while sipping coffee and planning the week ahead.
   
   Why This Workflow Matters  
   
   - 🧠 Memory Booster: Slack is ephemeral. This report brings forgotten conversations back into focus.  
   - 🔄 Asynchronous Friendly: Ideal for remote teams or teams across time zones.  
   - 💼 Project-Based Insights: Works best per channel/project; helps keep context intact.  
   - 🧩 Fully Customisable: Adjust tone, channels, and user filters to suit your team.
   
   How to Tailor It for Your Team  
   
   - Change the reporting tone: Make it formal for clients, or fun and casual for internal teams.  
   - Add performance metrics: Integrate KPIs or bug reports to align communication with results.  
   - Mail the report: If Slack is noisy, consider delivering it via email or as a PDF report.
   
   What You’ll Need  
   
   - A Slack workspace with an active channel  
   - Access to Google Gemini API  
   - An n8n instance with scheduled workflows
   
   Conclusion  
   
   This n8n workflow acts like a personal assistant for your entire team—watching activity unfold across Slack, capturing meaningful moments, and delivering a weekly roundup that no one has to create manually. It transforms team communication from transient chatter to actionable insight, saving time while improving awareness and morale.
   
   For project managers, this tool ensures decisions and blockers never slip through the cracks. For teams, it’s a useful Monday morning ritual to realign and refocus.
   
   Set it up once and let it run—your AI-powered project summary is just a Monday morning away.
   
   --- 
   
   Need Support? Join the n8n community on [Discord](https://discord.com/invite/XPKeKXeB7d) or browse the [n8n Forum](https://community.n8n.io/).

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.