/hybrid-search-implementation
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
One skill from wshobson-agents.
shell
$ npx -y skills add wshobson/agents --skill hybrid-search-implementation --agent claude-codeInstalls just this skill. Get the whole plugin for auto-invocation.
How it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/hybrid-search-implementation
Context preview
The summary Claude sees to decide when to auto-load this skill.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Stats
Stars38,174
Forks4,092
LanguagePython
LicenseMIT
Ships with wshobson-agents
SKILL.md
hybrid-search-implementation.SKILL.md
--- name: hybrid-search-implementation description: Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall. --- # Hybrid Search Implementation Patterns for combining vector similarity and keyword-based search. ## When to Use This Skill - Building RAG systems with improved recall - Combining semantic understanding with exact matching - Handling queries with specific terms (names, codes) - Improving search for domain-specific vocabulary - When pure vector search misses keyword matches ## Core Concepts ### 1. Hybrid Search Architecture ``` Query → ┬─► Vector Search ──► Candidates ─┐ │ │ └─► Keyword Search ─► Candidates ─┴─► Fusion ─► Results ``` ### 2. Fusion Methods | Method | Description | Best For | | ----------------- | ------------------------ | --------------- | | **RRF** | Reciprocal Rank Fusion | General purpose | | **Linear** | Weighted sum of scores | Tunable balance |
