[Beta] Import Linear Issues

Linear Issues Importer for Dust

The Linear Issues Importer for Dust is a powerful tool designed to seamlessly synchronize your Linear data with Dust.

This open-source script, available on GitHub at dust-tt/dust-labs/linear, automates the process of exporting all issues from Linear, along with related metadata such as comments, attachments, and history. It fetches comprehensive metadata, like so:

Issue Summary for ENG-123: Implement new authentication flow

Metadata:
Issue Details:
ID: abc123
Number: 123
Identifier: ENG-123
URL: https://linear.app/company/issue/ENG-123

Team & Project:
Team: Engineering (ENG)
Project: Authentication Overhaul
State: In Progress (Active)

Dates & Times:
Created: 2024-03-18T10:00:00.000Z
Updated: 2024-03-18T15:30:00.000Z
Started: 2024-03-18T11:00:00.000Z
Due Date: 2024-03-25

People:
Creator: Jane Smith ([email protected])
Assignee: John Doe ([email protected])
Subscribers: Alice Brown ([email protected]), Bob Wilson ([email protected])

Planning:
Priority: 2 (High)
Estimate: 5 points
Cycle: Sprint 45 (2024-03-18T00:00:00.000Z to 2024-03-29T23:59:59.999Z)
Labels: security, authentication

Description:
Implement new OAuth2-based authentication flow with support for multiple providers.
- Add OAuth2 client implementation
- Support Google and GitHub providers
- Implement token refresh logic
- Add user session management

Comments:
Comment by Alice Brown ([email protected]) - 2024-03-18T12:00:00.000Z
Should we also consider adding Microsoft OAuth support?
Reactions: 👍: 2, 💡: 1

Comment by John Doe ([email protected]) - 2024-03-18T13:15:00.000Z
Good suggestion. I'll create a follow-up ticket for that.

Recent History:
2024-03-18T11:00:00.000Z - John Doe
Changed status from "Todo" to "In Progress"

The script then formats and uploads this data to Dust.

This integration enables more effective use of Dust's capabilities for creating AI agents that can analyze trends, improve response times, and enhance overall response quality. The script is designed with rate limiting, filtering, and error handling in mind, ensuring reliable performance even with large volumes of Linear issues.