This article provides a complete, practical walkthrough of the Manual Schedule 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 Workflow Cleanup in n8n: A Guide to Deleting Old Executions
   
   Meta Description:  
   Learn how to automate the cleanup of outdated workflow executions in n8n using a custom-built workflow. This guide walks you through using schedule triggers, conditional logic, and the n8n API for smart automation maintenance.
   
   Keywords:  
   n8n workflow automation, n8n API, delete old executions, clean up n8n workflows, automate n8n tasks, execution management, n8n schedule trigger, n8n maintenance, n8n tutorial, n8n best practices
   
   Third-Party APIs Used:  
   - n8n API
   
   Article:
   
   Streamlining Automation: Automatically Deleting Old Executions in n8n
   
   As automation platforms like n8n grow in popularity, managing workflow performance and maintaining a tidy workspace becomes increasingly relevant. One of the most overlooked but crucial steps in automation management is routine cleanup—particularly the deletion of obsolete workflow executions. Every unnecessary stored execution consumes resources and makes the system harder to maintain over time.
   
   In this article, we’ll explore an n8n workflow that automates the deletion of workflow executions that are older than 10 days. Using schedule triggers, conditional logic, and native n8n API nodes, this custom workflow helps keep your execution logs lean, efficient, and clutter-free.
   
   📌 Why Does It Matter?
   
   Over time, n8n workflows can generate hundreds or thousands of executions—many of which become irrelevant after a short time. Unless you have logging requirements or retention policies requiring long-term storage, it's good practice to implement lifecycle management for executions. An automated cleanup reduces system load, improves performance, and simplifies debugging.
   
   🧠 Overview of the Workflow
   
   This automation is designed in n8n with the following logic:
   
   - It triggers either manually or on a schedule.
   - Then, it fetches all workflow executions.
   - Each execution is checked to see if it is older than 10 days.
   - If it’s old enough, it is deleted using the n8n API.
   - If not, nothing happens.
   
   Let’s break down how the workflow operates step-by-step.
   
   ✅ Step 1: Triggering the Workflow
   
   The workflow can be triggered in two ways:
   1. Manually (via the Manual Trigger node) for testing or on-demand cleanup.
   2. Automatically (with a Schedule Trigger node) at 4:44 AM daily.
   
   This dual-trigger setup enables flexibility in development and deployment.
   
   🔍 Step 2: Listing All Executions
   
   Immediately after the trigger, the “n8n list execution” node is used to fetch all previous workflow executions from your instance. This node utilizes the n8n API with credentials stored securely in the workflow. It returns all execution logs from the connected n8n environment.
   
   🧪 Step 3: Evaluate Execution Age with Conditionals
   
   Each execution’s timestamp is evaluated using an If node. The condition checks if the execution’s startedAt date is older than 10 days. This is achieved through a dynamic expression:
   
   new Date(Date.now() - 10 * 24 * 60 * 60 * 1000).toISOString()
   
   If the execution qualifies as older than 10 days, it will proceed down the “true” path; otherwise, it gets filtered out.
   
   🗑 Step 4: Deleting Executions That Are Too Old
   
   If the condition is met, the workflow uses the "delete execution" node to remove the specific execution from the system. This operation also uses the n8n API, passing in the execution ID from the previous step. This cleans up outdated logs without affecting current or valuable recent data.
   
   If the condition is not met, the execution flows into a 'No Operation' node—which ensures nothing is executed on that path, essentially acting as a safe null operation.
   
   🧰 Tools and APIs Used
   
   The workflow relies solely on n8n’s native capabilities and uses the n8n API for both listing and deleting executions. No external APIs or third-party services are required, making it a secure and native solution for cleanup automation:
   
   - n8n API — Used to list and delete executions within the instance.
   
   🧩 Benefits of This Setup
   
   - Efficiency: Automatically clears logs that are no longer needed.
   - System Health: Reduces storage usage and potential performance bottlenecks.
   - Customization: Can be easily adapted for different age filters or execution states.
   - Automation: Completely hands-free once deployed in production.
   - Modularity: Uses standard n8n nodes for easy extension.
   
   📣 Final Thoughts
   
   This workflow is an excellent example of the power of n8n’s internal API and how it can be used not only to perform tasks externally but to maintain itself internally. Regular cleanup of executions is a best practice for scaling and long-term operability. By using n8n to automate its own housekeeping, you avoid bloat and keep your automation workflows running smoothly.
   
   Whether you're an automation enthusiast or a DevOps professional, implementing a maintenance flow like this ensures your n8n environment remains robust, clean, and efficient for the long run.
   
   Happy automating! 🚀
   
   Do you want to copy this workflow into your own n8n instance? Consider exporting it directly and uploading it to jumpstart your automation maintenance today!

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.