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.
Profile →npx skills add wshobson/agents --skill hybrid-search-implementation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 | | **Cross-encoder** | Rerank with neural model | Highest quality | | **Cascade** | Filter then rerank | Efficiency | ## Templates and detailed worked examples Full template library and detailed worked examples live in `references/details.md`. Read that file when you need the concrete templates. ## Best Practices ### Do's - **Tune weights empirically** - Test on your data - **Use RRF for simplicity** - Works well without
- When to Use This Skill
- Core Concepts
- 1. Hybrid Search Architecture
- 2. Fusion Methods
- Templates and detailed worked examples
- Best Practices
- Do's
- Don'ts
What does the hybrid-search-implementation skill do?
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
How do I install it?
Run `npx skills add wshobson/agents --skill hybrid-search-implementation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From wshobson/agents, a repository with 38,479 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.