Scheduled Jira Issue Summarization and Processing

## Try it out
### This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store.
This can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort.

### How it works
* This template contains 2 separate flows which run continuously via schedule triggers.
* The first populates our Supabase vector store with resolved issues within the last day. This helps keep our vector store up-to-date and relevant for the purpose of finding similar issues.
* It does this by pulling the latest resolved issues from JIRA and populating the Supabase vectorstore with carefully chosen metadata. This will come in handy later.
* The second flow watches for stale, unassigned issues for the purpose of aut-assigning to a relevant team member.
* It does this by comparing the stale issue against our vector store of resolved issues with the goal of identifying which team member would have best context regarding the issue.
* In a busy team, this may net a few team members as possible candidates to assign. Therefore, we can introduce additional logic to count each team member's assigned, in-progress issues. This is intended to not overload our busiest members.
* The team member with the least assigned issues is pressumed to have the most capacity and therefore is assigned. A comennt is left in the issue to notify the team member that they've been auto-assigned due to age of issue.

### How to use
* Modify the project and interval parameters to match those of your use-case and team members.
* Add additional criteria before assigning to a team member eg. department, as required.

### Need Help?
Join the [Discord]({{ $env.WEBHOOK_URL }} or ask in the [Forum]({{ $env.WEBHOOK_URL }}

Happy Hacking!