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Actionable suggestions to improve your repository.

Types

  • Rule-based: Automated analysis based on metrics
  • AI-powered: LLM insights with confidence scores

Categories

  • Process: Workflow and review optimizations
  • Engagement: Contributor onboarding and recognition
    • Issue author participation
    • Review diversity improvements
    • Discussion engagement
  • Performance: Merge times and bottlenecks
  • Quality: Testing and documentation
  • Diversity: Expanding contributor base across different activities

Priority

🔴 High - Critical impact
🟠 Medium - Worth implementing
🔵 Low - Nice to have
Each card shows priority, description, confidence score, and action links.

Common Recommendations

Based on the enhanced health metrics, you may see recommendations like:
  • “Encourage more community members to report issues and provide feedback” (when issue engagement < 3 unique authors)
  • “Increase code review coverage to improve quality” (when review coverage < 50%)
  • “Expand your reviewer pool for better knowledge distribution” (when reviewer count is low)
  • “Improve contributor retention through better onboarding” (when bus factor is concerning)