Jira connection
What is the Jira connection?
Tabnine's AI chat allows you to connect to Atlassian Jira and extend the context of your chat with Jira issues. This capability enables you to ask Tabnine chat how to implement specific Jira issues or to validate whether your implementation aligns with the requirements detailed in those Jira issues. By bringing Jira into your IDE, you can streamline your workflow and minimize context-switching between different tools.
How to use the Jira connection
Step 1: Connect to Jira
First, you need to connect your Tabnine plugin in the IDE to your Jira account:
Open the Tabnine AI chat Settings. In your IDE, navigate to the Tabnine Chat Settings.
Under the settings, find the Jira section and click Connect.
Authorize access to Jira. A browser window will open, directing you to your Jira account. You’ll be prompted to give Tabnine access to your Jira workspace. Click Accept to confirm connecting Tabnine to your Jira.
After authorization, you’ll be redirected to the Tabnine web application.
Return to your IDE. In the chat settings, you can see that Jira has been successfully connected. There will also be an option to Disconnect.
Demo
You’re now ready to start using Jira in Tabnine Chat!
Step 2: Mentioning Jira issues in Tabnine Chat
Once the connection is established, all the Jira issues assigned to you as an individual user are available in Tabnine. Tabnine uses the existing Jira user permissions to ensure that only the issues assigned to you are available.
You can start referencing Jira issues in your chat prompts using any of these three triggers:
Type directly: Manually type
@Jira:
in the chat prompt.
For all triggers:
You’ll see a list of assigned Jira issues ordered by the last update.
You can filter the list by typing a prefix.
Hover for details: See the issue title when hovering.
Multiple mentions: Add more than one issue to a single prompt.
Does the Jira connection work with any issue format?
The Jira connection is flexible and doesn’t require issues to follow a strict template, but certain formats are more effective for producing relevant results. Here are some guidelines:
Optimized for:
Self-contained, smaller scope tasks
Specific tasks that include enough detail
Jira issues written in both formal and informal formats
Not optimized for:
Large, broad issues that lack specificity
General tasks without concrete details
Complex, multistep tasks without clear breakdowns
Examples
Not a good fit:
A good fit:
Use cases for Jira mentions
Implementing a Jira Issue:
Possible prompts:
Demo:
Code validation:
Possible prompts:
Demo:
Multiple issues mentions:
Possible prompts:
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