hybrid-search-implementation
hybrid search implementation
What it does
- 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
- Tune weights empirically - Test on your data
- Use RRF for simplicity - Works well without tuning
Requirements & configuration
- Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates.
- Don't assume one size fits all - Different queries need different weights
Derived from the skill's own SKILL.md documentation · extracted 2026-07-23
hybrid-search-implementation FAQ
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. Building RAG systems with improved recall Combining semantic understanding with exact matching
What does hybrid-search-implementation require?
Full template library and detailed worked examples live in references/details.md. Read that file when you need the concrete templates. Don't assume one size fits all - Different queries need different weights
How do I install hybrid-search-implementation?
Run: npx -y skills add https://github.com/wshobson/agents --skill hybrid-search-implementation --agent claude-code — the source lives at github.com/wshobson/agents.
Maintain hybrid-search-implementation?
Let people know it's listed here — add the badge (live metrics, light/dark aware) or a plain link to your README or docs.
[](https://getagentictools.com/skills/wshobson-agents-hybrid-search-implementation?ref=badge) npx agentictools info skills/wshobson-agents-hybrid-search-implementation The second line is the CLI lookup for this page — handy in READMEs and docs.
