This article provides a complete, practical walkthrough of the Schedule Filter Update 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:  
   Automate Your Task Management: Categorize and Prioritize Todoist Tasks with OpenAI in n8n
   
   Meta Description:  
   Discover how to streamline your productivity with this AI-powered n8n workflow that categorizes and prioritizes Todoist tasks using OpenAI’s GPT-4o-mini model.
   
   Keywords:  
   n8n workflow, Todoist automation, OpenAI GPT-4o-mini, task categorization, task prioritization, AI productivity, automated task manager, Todoist API, OpenAI API, productivity automation, GPT-4o task management, no-code workflow
   
   Third-Party APIs Used:
   
   - Todoist API
   - OpenAI API
   
   Article:
   
   Boost Your Productivity: Auto-Categorize and Prioritize Todoist Tasks Using n8n + OpenAI
   
   In today’s fast-paced digital world, keeping your task list organized can be challenging—especially when you’re juggling personal errands, work projects, and long-term goals. Fortunately, automation tools like n8n can help you save hours each week by streamlining repetitive workflows. In this article, we’ll explore an n8n workflow that intelligently categorizes tasks in Todoist and automatically assigns their priority level using OpenAI’s GPT-4o-mini model.
   
   If you’re using Todoist as your task manager and want to make your productivity smarter and more AI-enabled, this automation will be a game-changer.
   
   🧠 What This Workflow Does
   
   This n8n workflow analyzes each task in your Todoist Inbox, determines whether it belongs to a defined project category (like "apartment", "health", or "german") by using OpenAI's GPT-4o-mini model, and then sets the task’s priority accordingly. If a task doesn’t match any category or if the model misinterprets the task, the workflow safely skips assigning a priority—minimizing human error and AI hallucinations.
   
   🚀 Step-by-Step Breakdown
   
   Here’s how this automation workflow works in detail.
   
   1. Scheduled Trigger:  
   The workflow begins with a Schedule Trigger node. You can configure it to run periodically (e.g., every morning) to keep your tasks up to date.
   
   2. Define Projects and Priorities:  
   A Set node called “Your Projects” creates a mapping between project names and corresponding priority levels in Todoist. For instance, tasks related to “apartment” may have a lower priority (1), while “german” could have a higher urgency (3).
   
   Example:
   ```json
   {
     apartment: 1,
     health: 2,
     german: 3
   }
   ```
   
   3. Fetch Inbox Tasks from Todoist:  
   The "Get inbox tasks" node pulls all current tasks from your Todoist Inbox using the Todoist API. These are the tasks that haven't yet been filed under any specific project.
   
   4. Filter Subtasks:  
   Not all tasks need categorization—especially subtasks nested under parent tasks. The "If task is not a subtask" node filters out these subtasks based on the absence of a parent_id value.
   
   5. Send Task Content to OpenAI:  
   Each top-level task is sent to OpenAI’s GPT-4o-mini model via the “Categorize” node. The model is prompted to match each task to one of the provided project names or return “other” if it doesn’t fit.
   
   System Prompt Example:
   "Categorize the user's todo item to a project. Return the project name or just 'other' if it does not belong to a project."
   
   Dynamic Content Prompt:
   “Projects:
   apartment
   health
   german
   
   Todo item:
   Buy groceries”
   
   6. Validate Classification Output:  
   To avoid acting on an invalid or hallucinated category, a filter node called “If other or AI hallucinates” checks whether the returned project name matches one of the predefined categories. If it doesn’t, the task is ignored.
   
   7. Assign Priority in Todoist:  
   If the AI model's response is valid, the task is updated with the correct priority using the Todoist API via the "Update priority in Todoist" node.
   
   🛠 Setup Instructions
   
   To get started, you'll need to follow these steps:
   
   - Add Todoist credentials: Connect your Todoist API key to the relevant nodes.
   - Add OpenAI credentials: Securely link your OpenAI account for access to the GPT models.
   - Customize your project names and associated priorities inside the “Your Projects” node.
   
   💡 Use Case Scenarios
   
   - Professionals managing multiple responsibility areas like personal, work, and side-projects.
   - Students attempting to balance language learning, fitness, and coursework tasks.
   - Remote teams automating triage of incoming task items during daily standups.
   
   💬 Why Use GPT-4o-mini?
   
   GPT-4o-mini is a lighter and faster sibling of OpenAI’s GPT-4 family, designed to keep inference quick while retaining powerful contextual understanding. For something as dynamic as task categorization, where syntax may vary wildly (e.g., “doc appointment” or “renew rental contract”), GPT excels compared to traditional logic-based filters.
   
   🔐 Safety and Reliability
   
   The workflow includes intelligent filtering to minimize incorrect updates:
   - Skips subtasks to avoid over-modifying nested tasks.
   - Only proceeds with task updates if the AI output matches known project names.
   - Retry settings ensure tasks are not dropped due to transient API glitches.
   
   ✨ Final Thoughts
   
   This n8n workflow offers a hands-off way to bring structure and prioritization to your Todoist Inbox. By combining natural language understanding from OpenAI with the flexibility of n8n and the organizational power of Todoist, you can reclaim more time to actually work on your tasks—rather than organizing them.
   
   Ready to automate your task management? Clone the workflow, add your credentials, and start simplifying your productivity today.
   
   —
   
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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.