qmd

Index and search local Markdown collections with BM25 keyword search.

1|Updated Feb 2, 2026

Search Tags:#markdown #search #knowledge #notes #local #qmd

Ready to run

npx skills add https://github.com/KARENLHAO/skills --skill qmd-karenlhao

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: qmd
Source: https://github.com/KARENLHAO/skills/tree/main/qmd-skill
Command: npx skills add https://github.com/KARENLHAO/skills --skill qmd-karenlhao

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Local search for Markdown notes, docs, and knowledge bases to quickly find, relate, and retrieve content from indexed collections.

Core Features & Use Cases

Fast BM25 keyword search on local Markdown collections.
Optional semantic search using vector similarity for related content.
Indexing and retrieval of Markdown notes from indexed collections.

Quick Start

Index your Markdown collection with qmd and run a search query to retrieve relevant notes.

Frequently Asked Questions about qmd

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

FAQPage Schema

How do I search local Markdown notes and docs quickly?▼

To search local Markdown notes, you can index your collection and run a keyword query to retrieve relevant docs quickly. This provides fast BM25-based search across your local knowledge base files.

Can I use semantic search to find related content in Markdown notes?▼

Yes, you can use optional semantic search to find related content in Markdown notes. This feature uses vector similarity to discover related documents beyond exact keyword matches within indexed collections.

What is BM25 keyword search for local knowledge bases?▼

BM25 keyword search is the default ranking algorithm used to locate notes and docs in local Markdown collections. It indexes your files and retrieves specific documents based on term frequency and relevance.

How do I index a local Markdown collection for document retrieval?▼

You index a local Markdown collection by running the provided commands to scan and catalog your notes. This process prepares your docs for fast keyword search and optional embedding for semantic retrieval.

Does this local search tool require any external dependencies?▼

No, this local search tool requires no external dependencies to index and search Markdown collections. It operates entirely on your local machine using built-in commands for indexing, embedding, and maintenance.

When should I use semantic search versus BM25 for Markdown notes?▼

Use BM25 keyword search for fast exact term retrieval in Markdown notes, and switch to semantic search when you need to discover related content through vector similarity. Semantic search requires generating embeddings first.