🎯 Classify and convert GitHub issues to Jira tickets with OpenAI

⚡ 49 views · 🎯 AI Summarization & Classification

💡 Pro Tip — If you need GitHub data beyond what the REST API gives you, ScraperNode has a repository scraper that extracts metadata at scale without token rate limits.

Description

AI-Powered GitHub Issue to Jira Ticket Automation

Bridge the gap between your development and project management workflows with this intelligent n8n template. This isn’t just a simple sync; it uses an AI agent to analyze, classify, and intelligently route new GitHub issues into the correct Jira ticket type, saving you countless hours of manual triage.

🚀 Key Features

• AI-Powered Issue Classification: Leverages an AI Agent (powered by OpenAI) to analyze the content of a new GitHub issue and determine its type (e.g., bug, task, improvement).
• Intelligent Routing: Automatically creates the corresponding ticket type in Jira. Bugs in GitHub become Bugs in Jira; other issues become Tasks.
• Seamless Integration: Triggers instantly when a new issue is created in your specified GitHub repository.
• Rich Data Transfer: Migrates the issue title and body directly into the Jira ticket description for full context.
• Structured AI Output: Uses a structured output parser to ensure the AI’s classification is reliable and consistent.
• Beginner-Friendly & Educational: The workflow is annotated with sticky notes, explaining each step of the process, making it a great tool for learning how to use AI in n8n.

⚙️ How It Works

The workflow is designed for clarity and power, moving from issue creation to ticket generation in four automated steps.

1. Trigger: New GitHub Issue

• The GitHub Trigger node constantly listens for new issues being created in your designated repository. Once an issue is opened, the workflow springs into action.

2. Analyze: AI Classification

• The issue’s title and body are passed to an AI Agent.
• Using a prompt designed for classification and an OpenAI Chat Model, the agent determines if the issue is a bug, task, or another category.
• A Structured Output Parser ensures the AI returns clean, usable JSON data (e.g., {"type": "bug"}).

3. Route: Conditional Logic

• An IF node checks the structured output from the AI agent.
• If the type is “bug,” the workflow proceeds down the “bug” path. Otherwise, it follows the default path for “tasks.”

4. Create: Jira Ticket Generation

• Depending on the route, the corresponding Jira node is activated.
• A new ticket is created in your specified Jira project with the appropriate issue type (Bug or Task) and includes the full context from the original GitHub issue.

🛠️ Setup Steps & Credentials

To get this AI-powered workflow running, you’ll need to configure a few credentials:

1. GitHub:

   • Create a GitHub credential in n8n.
   • In the GitHub Trigger node, select your credential and specify the owner (your GitHub username or organization) and the repository you want to monitor.

2. OpenAI:

   • Obtain an API Key from platform.openai.com.
   • Create an OpenAI credential in n8n.
   • In the OpenAI Chat Model node, select your newly created credential. You can also experiment with different models like gpt-4.1-mini for speed or gpt-4o for higher accuracy.

3. Jira:

   • Create a Jira API token from your Atlassian account settings.
   • Create a Jira credential in n8n using your email, API token, and Atlassian domain.
   • In both the Create Jira Ticket (Bug) and Create Jira Ticket (Task) nodes, select your Jira credential and set your target project key.

💡 Customization & Learning

This workflow is a powerful starting point. Here are a few ways you can customize it and learn more:

• Expand Classification: Modify the AI Agent’s prompt and the IF node to handle more issue types, like improvement, documentation, or feature-request.
• Add More Data: Enhance the Jira nodes to include labels, assignees, or priority levels based on the AI’s output or the original GitHub issue’s properties.
• Swap AI Models: Try different language models by replacing the OpenAI node with one for Google Gemini, Anthropic Claude, or others supported by n8n.
• Error Handling: Add a path for what to do if the AI fails to classify an issue, such as sending a notification to a Slack channel for manual review.

📋 Requirements

• An active n8n instance.
• GitHub API credentials.
• OpenAI API credentials.
• Jira API credentials.

🔗 Nodes Used

Github Trigger, Jira Software, AI Agent, OpenAI Chat Model, Simple Memory, Structured Output Parser

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup