Automatically fix bugs in your backlog using coding agents (n8n + codecloud)

This guide covers a simple automation you can do with codecloud: when a ticket is created in Linear, an AI agent reads it, implements the changes, and opens a PR. No human in the loop until code review.

Codecloud handles the agent infrastructure, which is based on OpenCode. You can use any model supported by OpenCode, and any repository you have access to. n8n handles the integration with your issue tracker. This post walks through wiring them together.

This workflow could help you fix bugs in your backlog automatically, or even implement entire features for you (as long as each ticket has enough context).

How it works

n8n watches for new issues in Linear (or Jira). When one appears, it sends a request to codecloud with the ticket title and description as the prompt. codecloud spins up an agent, clones the repo, executes the task, and opens a PR.

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

Ticket quality matters

This workflow exposes bad tickets quickly. "Fix the bug" produces poor results. The agent needs a bit of context, the same way a developer would.

Effective tickets tend to include:

• A clear description of what should change
• Where in the codebase to look (or at least which feature area)
• Any constraints ("use the existing Button component")

As the workflow will run as soon as an issue is created, it's important to make sure the ticket is created with enough context from the start, rather than edited to add more context later.

Setup

Requirements: an n8n instance (cloud or self-hosted), a codecloud account with GitHub connected, and a Linear workspace. Jira setup is covered at the end.

First, 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_API_KEY

The workflow has two nodes. The Linear Trigger listens for new issues in a team. The HTTP Request node calls the codecloud API.

HTTP Request body:

{
  "repo": "your-org/your-repo",
  "prompt": "Please fix the bug or issue described in this ticket: 
 {{ $json.data.title }}\n\n{{ $json.data.description }}",
  "model": "claude-opus-4-5",
  "provider": "anthropic",
  "auto_create_pr": true
}

The expressions pull the title and description from the Linear webhook payload.

Importable workflow

The full workflow JSON is below. Import it in n8n via Workflows → Import from File, then update the placeholders (YOUR_TEAM_ID and your-org/your-repo) and attach credentials.

{
  "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],
      "credentials": {
        "linearApi": {
          "id": "1",
          "name": "Linear API"
        }
      }
    },
    {
      "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-opus-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],
      "credentials": {
        "httpHeaderAuth": {
          "id": "2",
          "name": "codecloud API"
        }
      }
    }
  ],
  "connections": {
    "Linear Trigger": {
      "main": [
        [
          {
            "node": "Create codecloud Run",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1"
  }
}

Filtering and options

The basic workflow fires on every new ticket. To filter, add an IF node after the trigger. For example, only process issues with a specific label like auto-pr.

Other useful options:

• "mode": "plan" – Returns an implementation plan without making changes. Useful for reviewing the approach before execution.
• webhook_url – Receive a notification when the run completes. Can be used to post the PR link to Slack or update the ticket.

Jira

Replace the Linear Trigger with a Jira Trigger (event: issue_created). Update the HTTP body expressions:

{
  "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
}

Jira's webhook payload structure differs, but the pattern is the same.

When this works well

With powerful LLMs like Opus 4.5, we're now seeing agents successfully implement not just bug fixes, but also entire features or products. Remember that the AI agents we use are only as good as the context they have: the more context you have in a ticket, the larger the successful changes you can expect.

The easiest way to try this workflow is to try it on your Backlog, filtered by a label like "auto-pr". This way you can see the results of the workflow without affecting your main backlog.

PRs won't always be correct. Some will miss the mark. But failed attempts often surface information about task complexity or edge cases that weren't obvious from the ticket.

For questions or feedback, use the support portal. For custom integrations, see the API documentation.