Qdrant Search Quality
SkillSearchLets your agent diagnose and improve the relevance of Qdrant vector search results.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Qdrant Search Quality skill
About this capability
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
What this skill tells your AI
The instructions your AI receives, as published by qdrant/skills in skills/qdrant-search-quality/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 232
- Forks
- 27
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
qdrant-search-quality- Source
- github.com/qdrant/skills