qdrant-search-quality
Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'how to combine keyword and vector search / fusion / RRF / prefetch?', 'should I use reranking?', 'relevance feedback?', 'how to measure retrieval quality?', 'build a golden set', 'ground truth dataset', 'how to score recall@k?', 'is my improvement real / statistically significant?', or 'should I fine-tune my embedding model?'. Also use when search quality degrades after quantization, model change, or data growth.
Pinned to revision 4e8964e24a5a, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
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- skills/qdrant-search-quality/SKILL.md
- skills/qdrant-search-quality/diagnosis/SKILL.md
- skills/qdrant-search-quality/search-strategies/SKILL.md
- skills/qdrant-search-quality/search-strategies/hybrid-search/SKILL.md
- skills/qdrant-search-quality/search-strategies/hybrid-search/combining-searches/SKILL.md
- skills/qdrant-search-quality/search-strategies/hybrid-search/search-types/SKILL.md
- skills/qdrant-search-quality/search-strategies/relevance-feedback/SKILL.md
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