Locate and retrieve Markdown notes from indexed collections using hybrid search.
npx skills add https://github.com/ninehills/skills --skill qmd-ninehills
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/ninehills/skills/tree/main/skills/qmd-skill Command: npx skills add https://github.com/ninehills/skills --skill qmd-ninehills
Locates and retrieves relevant Markdown notes and documents from indexed collections using a hybrid local search, reducing time spent scanning scattered folders.
Install qmd, index your notes, and start searching with a simple query.
High-intent search queries and answers about installing and using this skill.
You can search local Markdown notes by indexing your folders and running a query to retrieve relevant documents. This local hybrid search uses BM25 by default to locate specific files and cross-reference information across your knowledge base.
Local hybrid search works by indexing Markdown files and applying BM25 text matching to retrieve relevant documents. It optionally combines vector-based similarity search to improve semantic discovery of related content across your local folders.
Yes, indexing Markdown notes requires a local qmd binary and a Bun-based installation. You need this specific environment setup to build indexed collections and run fast queries against your personal knowledge base.
Yes, you can use optional vector-based similarity search alongside the default BM25 algorithm. This enables semantic search to find related content and retrieve specific documents from your project notes more effectively.
The best way to retrieve specific documents is to index your scattered Markdown folders into local collections. Once indexed, you can quickly locate and extract relevant notes using hybrid search instead of manually scanning directories.
alsk1992Search local Markdown notes with BM25, vector, and hybrid modes.
aivos-xieParse Markdown documents into a structured knowledge base for cross-referencing and queries.
icyzhRead, search, create, and edit markdown notes in Obsidian vaults.
sheawinklerSearch local markdown and text collections using hybrid BM25 and vector ranking.
