Index Markdown notes locally and search via keyword, semantic, or hybrid modes.
npx skills add https://github.com/MrGKanev/agent-skills --skill qmd-mrgkanev
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/MrGKanev/agent-skills/tree/main/skills/qmd Command: npx skills add https://github.com/MrGKanev/agent-skills --skill qmd-mrgkanev
This skill enables fast local search across Markdown notes, docs, and knowledge bases by indexing content on disk and enabling rapid retrieval.
Ensure Bun is installed and qmd is accessible on your system. Install and set up a local collection, then perform searches with qmd search, qmd vsearch, or qmd get as needed. Example: qmd search "project plan" -c notes
High-intent search queries and answers about installing and using this skill.
You can search local Markdown notes by indexing content on disk and running queries against the collection. This enables rapid retrieval of full documents or specific fragments from your personal knowledge base.
Yes, semantic search is supported for local Markdown documentation through an optional embedding setup. It matches user intent rather than just exact keywords, allowing for more flexible document retrieval.
You need the Bun runtime installed and a local qmd installation accessible on your system. Optional embedding setup is required if you want to use semantic search modes across your Markdown files.
The best way to retrieve specific fragments is using hybrid search modes. By indexing your Markdown notes on disk, you can query and extract exact document fragments for quick reference.
Yes, this approach works with large project documentation collections by indexing Markdown files on disk. It supports keyword, semantic, and hybrid search modes to match user intent across extensive knowledge bases.
Local Markdown search indexes content on disk to enable rapid retrieval and intent matching. Unlike standard file system search, it supports semantic and hybrid modes to retrieve full documents or specific fragments.
XSpoonAiIndex local notes with vector embeddings for offline semantic search.
jsphh7124Convert academic journals from PDF, Word, PowerPoint, Excel, images, and transcripts into structured Markdown.
Tommy-ywRead, search, and create notes in an Obsidian vault.
JuanMS20Index Markdown and text files for local hybrid search with BM25, vectors, and reranking.
