This article provides a complete, practical walkthrough of the Schedule Filter 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:
   Automate Task Prioritization in Todoist with AI Using n8n
   
   Meta Description:
   Learn how to automatically categorize and prioritize your Todoist tasks using n8n and OpenAI. This workflow uses AI to intelligently sort tasks into projects and set their priority—saving you time and effort.
   
   Keywords:
   Todoist automation, AI task management, n8n workflow, OpenAI GPT integration, todo list automation, task categorization, AI productivity tools, automate Todoist priorities, n8n Todoist OpenAI
   
   Third-Party APIs Used:
   
   - Todoist API
   - OpenAI API (via LangChain)
   
   Article:
   
   Automate Task Prioritization in Todoist with AI Using n8n
   
   Task overload is a common challenge for modern professionals. Whether you're juggling personal errands, work responsibilities, or learning goals, it’s easy to get lost in a long list of uncategorized to-dos. What if your task manager could automatically categorize and assign priorities to your tasks using artificial intelligence?
   
   With the power of n8n—a powerful open-source workflow automation tool—you can smartly automate task organization in Todoist using OpenAI's language model. This workflow taps into AI to determine the appropriate project category for a task and set a corresponding priority automatically.
   
   In this article, we’ll explore a fully automated n8n workflow that organizes your Todoist tasks with the help of OpenAI and categorizes them based on your defined projects.
   
   How It Works
   
   This workflow consists of several interconnected steps, intelligently orchestrated by n8n. Here's a breakdown of how it operates:
   
   1. Schedule Trigger
   At defined intervals (e.g., daily or hourly), the Schedule Trigger node kicks off the automation process. This ensures that your Todoist tasks are regularly checked and processed.
   
   2. Project Mapping
   A Set node, named Your Projects, defines the available project categories and correlates each to a priority level. For example:
   
   {
     apartment: 1,
     health: 2,
     german: 3
   }
   
   Each project is associated with a numeric priority (1 being the highest in Todoist). This map is used later to update the priority of tasks.
   
   3. Get Inbox Tasks
   The workflow queries your Todoist inbox (using the Todoist API) to retrieve all tasks that are currently uncategorized or not assigned to a specific project (by referencing a particular projectId for the inbox).
   
   4. Filter Out Subtasks
   A Filter node eliminates subtasks from being processed. Only parent-level tasks are considered for categorization to avoid unintentional misclassification and priority updates in nested task structures.
   
   5. AI-Powered Project Categorization
   This is where the magic happens. The task content is sent to OpenAI (via n8n’s LangChain integration), which has a system prompt asking it to return the most appropriate project name for the task. If the AI cannot match it with any known projects, it defaults to "other".
   
   System prompt used:
   “Categorize the user's todo item to a project. Return the project name or just ‘other’ if it does not belong to a project.”
   
   The task description is dynamically inserted into the AI query, and the AI model evaluates it against the list of known projects.
   
   6. Validation Check
   Once the OpenAI response is received, another Filter node ensures that the AI has returned a valid project name—i.e., one that actually exists in the user-defined “projects” object. This safeguards against “AI hallucinations,” or responses that are plausible but incorrect.
   
   7. Update Task Priority in Todoist
   Tasks that passed the validation step are then updated in Todoist with the appropriate priority score. The task’s priority is determined by the project-to-priority mapping defined earlier in the Your Projects node.
   
   Why This Is a Game-Changer
   
   ✔️ Saves Time: Manual tagging and prioritization of tasks takes mental energy and discipline. Automating it allows you to focus more on doing rather than organizing.
   
   ✔️ AI-Powered Categorization: By leveraging OpenAI's GPT capabilities, your tasks are intelligently categorized based on their content—even if you wrote them hurriedly or vaguely.
   
   ✔️ Always Current: With regularly scheduled checks, your Todoist inbox is always tidy, with categorized and prioritized tasks that reflect your defined focus areas.
   
   ✔️ Fully Customizable: Because this solution is created in n8n, you can easily expand it by adding notifications, tagging logic, deadlines, or syncing with other tools.
   
   Setup Instructions
   
   To implement this workflow, you’ll need:
   
   1. Todoist API Credentials
      Add your Todoist credentials via the n8n credential manager. These are used to access your tasks and update them accordingly.
   
   2. OpenAI API Key
      You’ll also need your OpenAI credentials (API key) to use the GPT-4 model for categorization.
   
   3. Define Your Categories
      Modify the Your Projects node to reflect the names of your projects and assign your preferred priority levels.
   
   Once these are set up, trigger the workflow manually or schedule it to run on a daily basis, and watch as your inbox gets neatly sorted—no additional effort required.
   
   Final Thoughts
   
   This n8n workflow is an excellent example of combining automation with AI to create smart productivity systems. By integrating Todoist and OpenAI, and injecting a bit of logical flow control, you’ve built an intelligent assistant that keeps your task inbox organized and actionable.
   
   Whether you’re a productivity enthusiast or someone just looking to streamline your planning routine, this workflow showcases how emerging tools can effortlessly optimize your life—one task at a time.
   
   Ready to take your productivity to the next level? Try integrating this AI-enhanced workflow and see how much more focused your day becomes.

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.