[Auto-Triage] Auto-Triage Report - January 31, 2026

[github-actions[bot]]

🏷️ Auto-Triage Report Summary

Report Period: January 31, 2026 00:45 UTC
Issues Processed: 1
Labels Applied: 3 total labels
Still Unlabeled: 0 issues

Key Metrics

• Success Rate: 100% (all issues successfully labeled)
• Average Confidence: High
• Most Common Classifications: refactoring (1), automation (1), good first issue (1)

Classification Summary

Issue	Applied Labels	Confidence	Key Reasoning
#12609	refactoring, automation, good first issue	High	Duplicate code analysis with clear refactoring plan, automated issue, beginner-friendly scope

View Detailed Classification Analysis

Issue #12609: Duplicate Code: Issue-closing REST calls across close_* scripts

Keywords Detected:

• "Duplicate Code Detected", "Refactoring Recommendations", "Extract a shared helper"
• "Implementation Checklist", "Estimated effort: 1-2 hours"
• "AI generated by Duplicate Code Detector"

Pattern Match:

• Textbook refactoring issue with clearly defined scope
• Automated code analysis output (mentions Serena semantic code analysis)
• Contains implementation checklist and effort estimates
• No new functionality, only code consolidation

Classification Reasoning:

1. refactoring (95% confidence):

   • Title explicitly mentions "Duplicate Code"
   • Body focuses on extracting shared helper functions
   • Impact analysis discusses "Maintainability" and "Code Bloat"
   • Clear statement: "code restructuring without behavior changes"

2. automation (100% confidence):

   • Footer states "AI generated by Duplicate Code Detector"
   • Created by github-actions[bot]
   • Part of automated workflow analysis

3. good first issue (85% confidence):

   • Clear implementation checklist with 6 specific steps
   • Estimated effort: 1-2 hours (small, bounded task)
   • Detailed code samples and locations provided
   • Well-defined scope: consolidate 3 similar functions
   • No complex architectural decisions required

Similar Issues: N/A (first duplicate code detector issue analyzed)

Overall Confidence Score: 93%

Label Distribution

• refactoring: 1 issue (100% of processed)
• automation: 1 issue (100% of processed)
• good first issue: 1 issue (100% of processed)

Recommendations

1. Monitor duplicate code detector output: This automated workflow generates well-structured issues that are ideal for auto-triage. Consider adding a rule to automatically apply automation + refactoring labels to issues created by this workflow.

2. Good first issue criteria validated: The issue meets all criteria for beginner-friendly tasks:

   • Clear, bounded scope with specific file locations
   • Effort estimates provided (1-2 hours)
   • Step-by-step implementation checklist
   • No complex architectural decisions

3. Success metrics achieved:

   • All unlabeled issues processed successfully
   • No needs-triage labels required
   • High confidence classification (93%)

Confidence Assessment

• Overall Success: High
• Human Review Needed: 0 issues flagged with needs-triage
• Next Steps: Continue monitoring for unlabeled issues. Current unlabeled rate: ~0.05% (1 out of ~2000 open issues) - well below 5% target.

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References: §21535673683

AI generated by Auto-Triage Issues

• expires on Feb 7, 2026, 12:47 AM UTC

[github-actions[bot]]

This discussion was automatically closed because it expired on 2026-02-07T00:47:17.070Z.