AI-Powered Automatic Issue Triage

[yusukebe]

Summary

Implement an AI system to automatically reproduce and classify GitHub issues, reducing maintainer workload and improving response times.

Motivation

• Many issues are "not a bug" but configuration/usage problems
• Maintainers spend significant time on initial triage
• Real bugs get buried in noise
• Current manual process doesn't scale with project growth

Proposed Solution

AI bot that:

1. Parses issue descriptions - Extract reproduction steps, environment details, expected vs actual behavior
2. Generates reproduction test code - Create minimal test cases based on issue description
3. Runs tests in sandbox environment - Execute tests across multiple runtimes (Node.js, Deno, Bun, Cloudflare Workers)
4. Auto-classifies issues - Categorize as: Bug/Not-a-bug/Need-info/Documentation

Benefits

• 80% reduction in manual triage time
• 24h initial response time for all issues
• Better focus on real bugs for maintainers
• Improved documentation derived from common mistakes
• Consistent quality of initial responses

Technical Approach

• GitHub Actions for automation
• Claude Code for AI processing and test generation
• Sandbox environment for safe test execution
• Multi-runtime testing for comprehensive validation

Community Impact

This could become a template for other OSS projects facing similar triage challenges.

Would love to get community feedback on this idea! 🚀

🤖 Generated with Claude Code