hybrid-search-implementation
Has your agent combine keyword and similarity searches. It's useful for improving accuracy in search and information retrieval systems.
What it does
This tool helps create search systems that understand both word meaning and the presence of exact terms. It combines two search methods to find information more comprehensively.
When to use it
- ✓When building systems that answer questions based on documents (RAG).
- ✓When you need search to find both general meaning and specific terms.
- ✓To improve search in areas with technical vocabulary or proper names.
Example of what to ask your AI
“How can I set up a search that understands meaning and also looks for exact keywords?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It works by combining meaning similarity search (vectors) with exact keyword search. This ensures both context and specific terms are considered.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill hybrid-search-implementationOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/hybrid-search-implementation/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
FAQ
What is vector search?
It's a search that understands the meaning behind words, finding texts that are semantically similar to your query, even if they use different words.
What is keyword search?
It's the traditional search that looks for the exact terms you typed in your query.
When is this combination better than a single search?
It's better when you need to ensure the search finds relevant information both by general meaning and by specific terms that might be missed by a single approach.
Details
Original description by the author
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Popularity
- GitHub stars
- 48k
- Ranking position
- #3300
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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