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.
Best use case
hybrid-search-implementation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Teams using hybrid-search-implementation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/hybrid-search-implementation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How hybrid-search-implementation Compares
| Feature / Agent | hybrid-search-implementation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this 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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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.md` for detailed patterns and examples.
Related Skills
searchnews
当用户要求"搜索新闻"、"查询AI新闻"、"整理新闻"、"获取某天的新闻"，或提到需要搜索、整理、汇总指定日期的AI行业新闻时，应使用此技能。
search-specialist
Expert web researcher using advanced search techniques and
research
Conduct preliminary research on a topic and generate research outline. For academic research, benchmark research, technology selection, etc.
research-report
Summarize deep research results into markdown report, cover all fields, skip uncertain values.
research-lookup
Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Automatically selects the best model based on query complexity. Search academic papers, recent studies, technical documentation, and general research information with citations.
research-grants
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC. Agency-specific formatting, review criteria, budget preparation, broader impacts, significance statements, innovation narratives, and compliance with submission requirements.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal impl...
research-deep
Read research outline, launch independent agent for each item for deep research. Disable task output.
research-add-items
Add items (research objects) to existing research outline.
research-add-fields
Add field definitions to existing research outline.
perplexity-search
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
notion-research-documentation
Searches across your Notion workspace, synthesizes findings from multiple pages, and creates comprehensive research documentation saved as new Notion pages. Turns scattered information into structured reports with proper citations and actionable insights.