qmd

Name: qmd
Availability: InStock
Author: mark

Index and search local notes, documents, and transcripts with hybrid retrieval.

31|3|Updated May 7, 2026

Search Tags:#mcp #notes #transcripts #knowledge-base #hybrid-search #local-search #qmd

Ready to run

npx skills add https://github.com/markwang2658/hermes-windows-native --skill qmd-markwang2658

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: qmd
Source: https://github.com/markwang2658/hermes-windows-native/tree/main/hermes-agent/optional-skills/research/qmd
Command: npx skills add https://github.com/markwang2658/hermes-windows-native --skill qmd-markwang2658

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Efficiently locate notes, documents, and transcripts across local collections using a hybrid retrieval engine that blends keyword search, vector semantics, and LLM reranking for high-quality results.

Core Features & Use Cases

Local-first search that works offline without cloud dependencies.
Hybrid retrieval combining BM25, vector search, and LLM reranking for precise results.
Use cases include personal knowledge management, meeting transcripts, and project documentation across multiple collections.

Quick Start

Run a sample hybrid search to find notes about onboarding.

Frequently Asked Questions about qmd

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

FAQPage Schema

How do I search personal notes and meeting transcripts locally without a cloud connection?▼

You can search personal notes and meeting transcripts locally without a cloud connection by using a local-first hybrid retrieval engine that operates offline. This approach indexes your isolated datasets across multiple collections to deliver search results without any cloud dependencies.

How does hybrid search work for finding specific project documentation across multiple local collections?▼

Hybrid search for local collections works by blending BM25 keyword search, vector semantic search, and LLM reranking. This combination retrieves and ranks precise results from your project documentation by matching both exact terms and contextual meaning.

Can I use MCP integration to query my local knowledge base?▼

Yes, you can use MCP integration to query your local knowledge base. The system supports both a CLI interface and MCP integration, allowing you to access indexed notes, documents, and transcripts through your connected workflow.

Do I need an internet connection to use vector search on my local documents?▼

No, you do not need an internet connection to use vector search on your local documents. The local-first search engine uses embedded models to perform vector semantic retrieval and LLM reranking entirely offline.

What is the best way to organize isolated datasets like notes and docs for local search?▼

The best way to organize isolated datasets like notes and docs for local search is to group them into local collections with context metadata. This allows the hybrid retrieval engine to effectively index and search across your personal knowledge base.

When should I not use a local hybrid search for my personal knowledge management?▼

You should not use a local hybrid search if your personal knowledge management requires collaborative multi-user access or centralized cloud synchronization. This approach is designed for isolated datasets on local machines rather than shared remote environments.