qmd

Retrieve local markdown documents via BM25, vector search, and hybrid ranking.

1|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/jannolan200211-ship-it/my-cosmos-backup --skill qmd-jannolan200211-ship-it
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: qmd
Source: https://github.com/jannolan200211-ship-it/my-cosmos-backup/tree/main/03%20Reference/02%20System%20Configs/skills/qmd-cli
Command: npx skills add https://github.com/jannolan200211-ship-it/my-cosmos-backup --skill qmd-jannolan200211-ship-it

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Local researchers and teams struggle to search scattered markdown notes, docs, and transcripts across personal machines.

Core Features & Use Cases

  • BM25 keyword search for fast exact matches on local Markdown files.
  • Vector semantic search and hybrid ranking to find conceptually related content.
  • Use cases include querying notes, documentation, and meeting transcripts from local knowledge bases.

Quick Start

Install the qmd CLI globally and start indexing your markdown collections to enable fast local search.

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 documentation effectively?

Local markdown search is enabled by indexing files with the qmd CLI, utilizing BM25 for exact keyword matches and vector search for semantic ranking. This provides hybrid retrieval across notes, docs, and transcripts.

What is the best way to find conceptually related content in local markdown files?

Vector semantic search and hybrid ranking find conceptually related content in local markdown files by matching meaning rather than just keywords, ideal for scattered notes and meeting transcripts.

Do I need to install any dependencies to index markdown meeting transcripts locally?

Yes, you need to install the qmd CLI globally to index markdown meeting transcripts locally, which then outputs JSON results for integration with your existing tools and workflows.

Can I use BM25 keyword search for exact matches on local markdown knowledge bases?

Yes, BM25 keyword search provides fast exact matches on local markdown knowledge bases, allowing engineers and researchers to quickly query indexed documentation and notes.

How do I integrate local markdown search results with other engineering tools?

You integrate local markdown search results using the JSON output format provided by the qmd CLI, enabling seamless data passing to downstream engineering tools and automation pipelines.