This article provides a complete, practical walkthrough of the Code Filter Create Webhook 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 Issue Importing from Notion to Linear with n8n: A Workflow Deep Dive
   
   Meta Description:
   Discover how to streamline issue tracking with a powerful n8n automation that converts Notion to-do items into Linear issues—complete with Markdown formatting, assignments, and bidirectional sync.
   
   Keywords:
   
   - n8n automation
   - Notion to Linear integration
   - project management automation
   - Notion API
   - Linear API
   - GPT-4 title summarization
   - Notion to-do parser
   - n8n workflow tutorial
   - AI workflow automation
   - issue tracking integration
   
   Third-Party APIs Used:
   
   1. Notion API – For reading to-do items and updating blocks
   2. Linear GraphQL API – For querying teams, creating and retrieving issues
   3. OpenAI API (GPT-4) – For shortening long titles to meet Linear constraints
   
   Article:
   
   Streamlining Project Management: Automating Notion-to-Linear Issue Creation with n8n
   
   In many modern teams, Notion serves as a flexible workspace to brainstorm, plan, and structure project tasks, while Linear takes the lead for issue tracking and sprint-based execution. Manually transferring tasks from Notion to Linear can be tedious and error-prone—but what if this process could be fully automated? Enter n8n, the open-source workflow automation tool.
   
   In this article, we explore a comprehensive n8n workflow that ingests unchecked to-do items from Notion and automatically creates detailed issues in Linear, complete with Markdown-formatted descriptions, intelligently parsed assignees, concise GPT-generated titles, and a feedback loop that updates the original Notion content with the Linear issue link.
   
   Let’s walk through the inner workings of this automation and how it leverages integrations with Notion, Linear, and OpenAI.
   
   📋 Step 1: Capturing Form Inputs
   
   The workflow begins with a Form Trigger in n8n, prompting the user to select:
   - A Notion page URL where tasks are defined
   - A Linear team (from predefined options like AI, Adore, Payday, NODES)
   
   This ensures the process is scoped to the correct page and team context.
   
   📡 Step 2: Fetching and Filtering Input Data
   
   The workflow uses the Notion API to retrieve all blocks from the specified page. These blocks are filtered to isolate unchecked to-do items that haven’t already been imported to Linear (i.e., items not starting with “[In Linear]”).
   
   Simultaneously, the workflow queries the Linear GraphQL API to get metadata about the specified team—its ID, current members, and existing projects. This data is crucial for assigning tasks and linking them appropriately in Linear.
   
   ❓ Step 3: Handling Errors Gracefully
   
   If the specified Linear team isn’t found or the Notion page can’t be accessed by the integration (e.g., it's not shared), the workflow halts and pings the user with a helpful error message—maintaining transparency and usability.
   
   🧠 Step 4: Parsing To-Do Content and Assignments
   
   Next comes a smart text parsing step. Each Notion to-do is inspected for potential assignee references in its first line. For example, “[Alice] Fix broken navbar” would assign the task to a team member whose name starts with "Alice". The script extracts this name fragment and checks it against the list of Linear team members. If a match is found, the assignee ID is captured for later use in issue creation.
   
   ✂️ Step 5: Title Shortening via GPT-4
   
   Linear imposes a soft character limit on issue titles. If the parsed title exceeds 70 characters, it is automatically sent to OpenAI’s GPT-4 model using the LangChain n8n node, which returns a shortened, more concise version. This ensures readability and prevents API errors from overloaded titles.
   
   🖋️ Step 6: Building Markdown Descriptions
   
   The workflow collects all children blocks under the to-do item and converts them into well-structured Markdown. It handles bullets, list types, images, videos, and nested items—all hierarchically indented to maintain the original structure. This makes the issue readable and informative when viewed in Linear.
   
   ✍️ Step 7: Composing and Creating the Issue
   
   Once the title and description are ready, an issue is created in Linear using the team ID, assignee ID, and the Markdown-rich description. It even includes a backward link to the Notion block from which the task originated—a complete audit trail.
   
   🔄 Step 8: Updating Notion with Issue Link
   
   After the issue is created, the Linear GraphQL API is queried for the newly generated issue URL. This link is added back to the original Notion to-do block, updating its content to `[In Linear]` format, effectively marking it as imported and providing quick navigation.
   
   🔁 Step 9: Looping Through All Items
   
   The entire flow loops through each unprocessed to-do item, ensuring that all tasks are accounted for and none are duplicated. This loop is structured using n8n’s Split In Batches node to handle items one at a time for performance and error handling.
   
   💡 Summary & Benefits:
   
   - Seamlessly bridges Notion’s planning space with Linear’s execution platform.
   - Reduces duplication of effort and manual syncing.
   - Ensures accurate data mapping: assignees, task context, hierarchy.
   - Leverages OpenAI for better UX via smart title management.
   - Provides full traceability with linked updates in both systems.
   
   By combining robust APIs with n8n’s visual workflow builder, this automation offers teams a scalable and transparent way to keep their tools in sync—improving productivity and reducing overhead.
   
   Whether you’re dealing with a design review checklist or feature backlog, this solution helps you stay organized across platforms—automatically.
   
   Ready to try it? Make sure your Notion page is shared with the integration and click 'Test Workflow' in your n8n environment.
   
   —
   
   By harnessing the power of APIs and automation, this use case demonstrates how n8n workflows can transform routine tasks into intelligent, connected operations.

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.