hybrid-search-implementation
Implements more efficient hybrid retrieval functions by combining vector and keyword search. (AI Agent Skill for efficiency and automation)
npx skills add sickn33/antigravity-awesome-skills --skill hybrid-search-implementationBefore / After Comparison
1 组Traditional keyword search or standalone vector search often struggles to provide the most relevant results in certain complex scenarios. Users frequently encounter issues with insufficient search precision and low recall rates, impacting information retrieval efficiency.
Now, by combining vector and keyword hybrid search, the accuracy and relevance of information retrieval can be significantly enhanced. This approach integrates the advantages of both methods, ensuring users can quickly find content that best meets their needs.
description 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." risk: unknown source: community date_added: "2026-02-27"
Hybrid Search Implementation
Patterns for combining vector similarity and keyword-based search.
Use this skill when
- 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
Do not use this skill when
- The task is unrelated to hybrid search implementation
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
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