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Problem Statement
Inspired by how Claude integrates LLM-powered automation to streamline issue management, we’d like to bring a similar approach to this project. Currently, issue triage and duplicate detection require manual effort, which can be repetitive and time-consuming. By leveraging automation, we can reduce overhead, improve backlog quality, and provide a smoother contributor experience.

Goal
- Auto-triage new issues: Automatically apply appropriate labels based on detected keywords, platform, or error type
- Auto-close duplicates: Detect and close duplicate issues with links to the original thread, while notifying the reporter.
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