UI はローカライズ済みです。スキルの紹介と説明文書は選択した言語へ AI が自動翻訳し、コード・コマンド・パス・専門用語は原文のままです。原作者の文書が優先されます。
スキルを探す
データ・研究 · SKILL.md

qdrant-search-quality

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?', 'should I use reranking?'. Also use when search quality degrade…

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: qdrant-search-quality description: "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?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth." allowed-tools:

  • Read
  • Grep
  • Glob

Qdrant Search Quality

First determine whether the problem is the embedding model, Qdrant configuration, or the query strategy. Most quality issues come from the model or data, not from Qdrant itself. If search quality is low, inspect how chunks are being passed to Qdrant before tuning any parameters. Splitting mid-sentence can drop quality 30-40%.

  • Start by testing with exact search to isolate the problem Search API

Diagnosis and Tuning

Isolate the source of quality issues, tune HNSW parameters, and choose the right embedding model. Diagnosis and Tuning

Search Strategies

Hybrid search, reranking, relevance feedback, and exploration APIs for improving result quality. Search Strategies

保存したスキル