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Key optimizations:

  • Dynamic query detection: Identify 'all' and 'complete' questions
  • Smart fact limits: 50 facts for comprehensive questions, 25-40 for others
  • Fact prioritization: Policy/convention keywords ranked first
  • Optimized formatting: Compact bullets, filtered noise
  • Context-aware limits: Reduce entities on hard questions to save space

Results:

  • Hard category: 25% (5/20 correct)
  • Overall: 60% (36/60 correct)
  • Completeness: 58.3% complete, 41.7% partial
  • When complete: 97.1% accuracy

Approach is generalizable to any developer, not overfitted to test data.

Contest Submission

Submission Checklist

  • I agree to license my submission under the MIT License
  • My PR title follows the required format: XX.XX% - Title (where XX.XX% is my hard category accuracy score)
  • I recognize my solution can be rejected if it fails to comply with any of the rules specified in the README

Approach Description (Optional)

Key optimizations:
- Dynamic query detection: Identify 'all' and 'complete' questions
- Smart fact limits: 50 facts for comprehensive questions, 25-40 for others
- Fact prioritization: Policy/convention keywords ranked first
- Optimized formatting: Compact bullets, filtered noise
- Context-aware limits: Reduce entities on hard questions to save space

Results:
- Hard category: 25% (5/20 correct)
- Overall: 60% (36/60 correct)
- Completeness: 58.3% complete, 41.7% partial
- When complete: 97.1% accuracy

Approach is generalizable to any developer, not overfitted to test data.
@NikkiAung NikkiAung changed the title Optimize context retrieval: 25% hard category accuracy 25% hard category accuracy : Optimize context retrieval Dec 11, 2025
@NikkiAung NikkiAung changed the title 25% hard category accuracy : Optimize context retrieval 25% hard category accuracy : Optimize context retrieval (Used trick of Multithreading & Parameter Optimization Strategy) Dec 11, 2025
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