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Robin Bilgil
Robin Bilgil

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How I automated my bug backlog with n8n and a coding agent API

#n8n #automation #ai #github

Every team has a backlog of bugs that never get prioritized. From small bugs like typos, missing error messages, broken links, minor UI glitches (stuff that's easy to fix but never urgent enough to schedule), to larger problems that come with a customer support ticket attached, it's hard to put these fixes ahead of business priorities.

To solve this in the age of AI, I built a workflow on top of OpenCode that processes these automatically. When a ticket is created in Linear with a specific label, an AI coding agent reads it, implements the fix, and opens a pull request. If the ticket has extra context, that feeds into the fix.

Here's how it works and how to set it up.

The architecture

The workflow has three pieces:

  • Linear (or Jira) as the trigger — a new ticket fires a webhook
  • n8n as the orchestrator — receives the webhook, sends the API call
  • CodeCloud as the execution layer — spins up an AI agent (OpenCode), clones the repo, implements changes, opens a PR

The n8n workflow is literally two nodes: a trigger and an HTTP request.

Why this is useful

The obvious objection: "AI can't fix real bugs." And yeah, if the ticket says "fix the bug" with no other context, the result is garbage. But that's true for human developers too.

What works surprisingly well:

  • Well-described bugs — "The signup button doesn't submit on Safari because we're using FormData without a polyfill" → the agent finds the file, adds the polyfill, opens a PR
  • Tedious changes — "Update all error messages to use the new i18n format" → the agent greps, updates, opens a PR
  • Documentation — "Add JSDoc comments to all exported functions in /lib" → mechanical work the agent handles well

The key insight: ticket quality determines output quality. This workflow forces your team to write better tickets, which is a side benefit even when the agent misses.

Setup

You'll need:

  • An n8n instance (cloud or self-hosted)
  • A CodeCloud account with GitHub connected
  • A Linear (or Jira) workspace

Step 1: Add credentials in n8n

For Linear, create an API key from Settings → API → Personal API keys.

For CodeCloud, create a Header Auth credential:

  • Name: Authorization
  • Value: Bearer YOUR_CODECLOUD_API_KEY

Step 2: Build the workflow

The workflow is two nodes:

Node 1: Linear Trigger

  • Resource: Issue
  • Team: Select your team

Node 2: HTTP Request

  • Method: POST
  • URL: https://codecloud.dev/api/v1/agents
  • Authentication: Header Auth (the credential you created)
  • Body (JSON): 
{
  "repo": "your-org/your-repo",
  "prompt": "Please fix the bug or issue described in this ticket: \n {{ $json.data.title }}\n\n{{ $json.data.description }}",
  "model": "claude-sonnet-4-5",
  "provider": "anthropic",
  "auto_create_pr": true
}
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The {{ $json.data.title }} and {{ $json.data.description }} expressions pull the ticket content from Linear's webhook payload.

Step 3: Add filtering (recommended)

The basic workflow fires on every new ticket, which you probably don't want. Add an IF node between the trigger and the HTTP request:

  • Condition: {{ $json.data.labelIds }} contains your auto-pr label ID

This way only tickets explicitly tagged for automation get processed.

Importable workflow JSON

You can import this directly in n8n via Workflows → Import from File:

{
  "name": "Linear to CodeCloud PR",
  "nodes": [
    {
      "parameters": {
        "resource": "issue",
        "teamId": "{{ YOUR_TEAM_ID }}"
      },
      "id": "linear-trigger",
      "name": "Linear Trigger",
      "type": "n8n-nodes-base.linearTrigger",
      "typeVersion": 1,
      "position": [240, 300]
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://codecloud.dev/api/v1/agents",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={\n  \"repo\": \"your-org/your-repo\",\n  \"prompt\": \"Please fix the bug or issue described in this ticket: \\n {{ $json.data.title }}\\n\\n{{ $json.data.description }}\",\n  \"model\": \"claude-sonnet-4-5\",\n  \"provider\": \"anthropic\",\n  \"auto_create_pr\": true\n}"
      },
      "id": "http-request",
      "name": "Create CodeCloud Run",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.2,
      "position": [480, 300]
    }
  ],
  "connections": {
    "Linear Trigger": {
      "main": [[{ "node": "Create CodeCloud Run", "type": "main", "index": 0 }]]
    }
  }
}
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Update YOUR_TEAM_ID and your-org/your-repo, then attach your credentials.

Jira variant

Replace the Linear Trigger with a Jira Trigger (event: issue_created). Update the body expressions to match Jira's payload:

{
  "repo": "your-org/your-repo",
  "prompt": "{{ $json.issue.fields.summary }}\n\n{{ $json.issue.fields.description }}",
  "model": "claude-sonnet-4-5",
  "auto_create_pr": true
}
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Useful options

A couple of API parameters worth knowing:

  • "mode": "plan" — Returns an implementation plan without making changes. Good for reviewing the approach before letting the agent execute.
  • webhook_url — Get notified when the run finishes. You can use this to post the PR link back to Slack or update the Linear ticket status.

Honest results

These fixes will sometimes miss the mark or need further iteration. But I've found that even failed attempts surface useful information. They expose ambiguity in tickets, reveal edge cases nobody considered, and often get 80% of the way there so a developer can finish the last 20% in minutes.

The easiest way to try this: create an auto-pr label in Linear, tag a few well-described bugs from your backlog, activate the workflow, and see what happens. Worst case, you close a few bad PRs. Best case, you clear a chunk of your backlog before lunch.

CodeCloud is an API for running AI coding agents. If you have questions or want to share what you've built, drop a comment below or check out the docs.

Top comments (3)

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nedcodes profile image
Ned C •

the n8n orchestration layer is interesting. how do you handle cases where the agent's fix introduces a regression? do you have a test suite gate before the PR gets created, or is it more of a draft-PR-for-review workflow?

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rbilgil profile image
Robin Bilgil •

Thanks. It's more draft-PR-for-review at the moment, though at the CI level I have lint, unit and e2e tests that should catch basic regressions, and usually get everything deployed to a preview branch to test it manually as well (these days using Convex + Vercel which makes this easy too!)

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nedcodes profile image
Ned C •

does convex handle the database state for previews or do you seed test data separately? that's usually where automated PR pipelines break down for me, the code change is fine but the test data doesn't match production shape