qmd

Perform local semantic searches across notes and project documentation.

34|2|Updated Feb 24, 2026
One-click install
npx skills add https://github.com/retran/meowary --skill qmd-retran
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: qmd
Source: https://github.com/retran/meowary/tree/main/.shared/skills/qmd
Command: npx skills add https://github.com/retran/meowary --skill qmd-retran

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides local semantic search capabilities for notes, resources, and projects, improving information retrieval efficiency.

Core Features & Use Cases

  • Semantic Search: Perform keyword or natural language queries to find relevant content across collections.
  • Query Types: Use lex, vec, or hyde query types to target exact, semantic, or hypothetical answers.
  • Use Case: Quickly locate relevant project notes or research articles by asking natural language questions or keyword searches within your digital archive.

Quick Start

Use the qmd skill to perform a semantic search for your notes or project documents with a simple query.

Frequently Asked Questions about qmd

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform local semantic search across my project notes and documentation?

Local semantic search across project notes is performed using command-line tools to execute queries. You can use keyword or natural language queries to retrieve relevant information from your indexed collections.

What is the difference between lex, vec, and hyde query types for knowledge management?

Lex, vec, and hyde query types target exact matching, semantic similarity, and hypothetical answers respectively. Choosing the right query type helps locate relevant resources based on different search intents.

Can I use this semantic search tool for my existing local notes and resources?

Yes, you can use this semantic search tool for your local notes and resources. It integrates with command-line tools to maintain your index and execute precise information retrieval across your digital archive.

What's the best way to maintain an organized knowledge base for local search?

The best way to maintain an organized knowledge base is by using the integrated command-line index maintenance tools. Regular indexing ensures your project documentation and notes remain searchable and up-to-date.

Does local semantic search work without relying on external cloud services?

Local semantic search works directly on your machine without relying on external cloud services. It processes your notes and project documentation locally to provide efficient and private information retrieval.

What are the limitations of using command-line tools for semantic indexing?

Using command-line tools for semantic indexing requires manual execution for index maintenance and search operations. Users must be comfortable with CLI environments to fully utilize the lex, vec, and hyde query capabilities.