This article provides a complete, practical walkthrough of the Filter Slack 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:
   Automated Bug Triage in Linear Using n8n and OpenAI
   
   Meta Description:
   Discover how to automate bug triage and team assignment in Linear using a custom n8n workflow integrated with OpenAI and Slack. Streamline your incident management process and improve team productivity.
   
   Keywords:
   n8n automation, Linear bug triage, OpenAI GPT-4 workflow, Slack notifications, AI ticket classification, Linear API, OpenAI API, triage automation, bug classification, team assignment automation
   
   Third-Party APIs Used:
   
   - Linear API
   - OpenAI API
   - Slack API
   
   Article:
   
   Automated Bug Triage in Linear Using n8n and OpenAI
   
   As software development teams scale, so do the number of issues reported by users. These bug reports can quickly become overwhelming, especially when your teams are separated by areas of responsibility. Manually reading each bug ticket, understanding its context, and forwarding it to the appropriate team wastes valuable time and introduces the risk of human error.
   
   What if you could automate this entire workflow? Enter n8n — a powerful workflow automation tool — paired with OpenAI’s GPT-4 model and third-party integrations like Linear and Slack. In this article, we'll walk through a robust n8n workflow that automatically triages Linear bug tickets using AI and routes them to the right team, notifying stakeholders where needed.
   
   The Goal: Fully Automated Bug Classification
   
   The purpose of this workflow is to:
   1. Monitor new bug tickets submitted in Linear.
   2. Evaluate whether the ticket is ready for classification (i.e., contains a valid description, correct status, and required labels).
   3. Use OpenAI to analyze ticket content and determine the appropriate team.
   4. Update the Linear issue, moving it to the responsible team.
   5. Notify a Slack channel if AI cannot confidently classify the issue.
   
   Breaking Down the Workflow
   
   Let’s dig into the key components that make this workflow possible:
   
   1. Linear Trigger
   The journey begins with the Linear Trigger node. It listens for new or updated tickets within a specified team that match the "issue" resource. This sets off the chain reaction whenever a new bug report is created.
   
   2. Filtering Unready Tickets
   The “Only tickets that need to be classified” node uses a series of conditional filters to make sure the ticket meets triage criteria. It passes only those issues that:
   - Don’t contain placeholder text like “Add a description here.”
   - Are labeled with a "Triage" state.
   - Include a “type/bug” label.
   
   Any ticket that fails these conditions is excluded from further processing, keeping the workflow clean and focused.
   
   3. Preparing Teams and Context
   The “Set me up” node is central to customizing your pipeline. Here, you define team names alongside their areas of responsibility using a specific format: [TeamName][Description].
   
   For example:
   - [Adore][Handles everything outside of Enterprise like signup flows, NDV, workflows UI]
   - [Payday][Takes care of Enterprise-specific features like SSO, SAML, external storage]
   - [Nodes][Manages all node-specific functionalities]
   
   This node also defines your target Slack channel for notifications.
   
   4. AI-Powered Team Classification (Using OpenAI)
   When a valid bug report makes it through, it’s handed off to OpenAI’s GPT-4. The AI model receives a system prompt that includes the list of all teams along with the detailed bug description (title and body). It is then asked:
   "Which team should work on this bug?"
   
   GPT-4 responds with the name of a team from the pre-defined list. Thanks to the well-structured prompt, the AI consistently returns a valid team, making it ideal for automation.
   
   5. Validating AI Output
   The “Check if AI was able to find a team” IF node determines if the AI returned a valid team name or defaulted to “Other.” If it’s a valid match, the workflow proceeds to fetch internal Linear team IDs using the “Get all linear teams” node (via the Linear GraphQL API).
   
   6. Reassigning the Ticket
   Through the “Set team ID” and “Update team” nodes, the Linear issue is updated to change its owning team. This ensures clean hand-offs between QA or support and the development team best suited to resolve the issue.
   
   7. Slack Notifications for Unresolved Assignments
   If GPT-4 returns “Other” — meaning it couldn’t confidently classify the bug — the workflow routes to a Slack node to notify a specified channel. This human-in-the-loop fallback ensures no ticket goes unresolved due to automation uncertainty.
   
   Customization and Setup
   The workflow is highly customizable. Here’s what you’ll need to do to get it running for your organization:
   - Add your Linear and OpenAI credentials.
   - Define your Linear team ID for the trigger node.
   - Configure your teams in the “Set me up” node with accurate names and roles.
   - Define your Slack channel for notifications.
   
   Benefits of This Approach
   
   - Consistent Classification: AI models like GPT-4 provide objective and comprehensive analysis of bug descriptions, ensuring classification accuracy.
   - Scalability: The system scales effortlessly, handling hundreds of tickets a day without human input.
   - Reduced Manual Work: Engineers no longer need to route tickets manually or organize triage sessions.
   - Real-Time Notification: Teams are immediately updated about misclassified tickets that need their attention, thanks to Slack integration.
   
   Conclusion
   
   By automating bug triage in Linear with the help of n8n and OpenAI, you save time, reduce errors, and ensure the right teams are looped in faster. With added Slack notifications for oversight and flexible customization options, your bug management process becomes smarter and more efficient.
   
   If you’re already using Linear, Slack, and OpenAI, this n8n workflow is a powerful step toward intelligent, automated product development operations.
   
   Start automating your triage today and let AI do the ticket reading — your teams will thank you.

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.