How do I install the Qmd skill?

Run npx skillmds@latest add demerzels-lab/qmd in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Qmd?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Demerzels-lab (@demerzels-lab) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Qmd by demerzels-lab — Agent Skill

Name: Qmd
Author: Demerzels-lab

Qmd

Search and retrieve markdown documents from local knowledge bases using qmd. Supports BM25 keyword search, vector semantic search, and hybrid search with LLM re-ranking. Use for querying indexed notes, documentation, meeting transcripts, and any markdown-based knowledge. Requires qmd CLI installed (bun install -g https://github.com/tobi/qmd).

Demerzels-lab aa92190 2 files · 3.0 KB Updated Sep 17, 2026 10 repo stars

File contents

QMD - Local Markdown Search

Search and retrieve documents from locally indexed markdown knowledge bases.

Installation

bun install -g https://github.com/tobi/qmd

Setup

# Add a collection
qmd collection add ~/notes --name notes --mask "**/*.md"

# Generate embeddings (required for vsearch/query)
qmd embed

Usage Rules

Always use --json flag for structured output when invoking qmd commands.

Search Commands

search (BM25 keyword search - fast)

qmd search "authentication flow" --json
qmd search "error handling" --json -n 10
qmd search "config" --json -c notes

vsearch (vector semantic search)

qmd vsearch "how does login work" --json
qmd vsearch "authentication best practices" --json -n 20

query (hybrid with LLM re-ranking - best quality)

qmd query "implementing user auth" --json
qmd query "deployment process" --json --min-score 0.5

Search Options

Option	Description
`-n NUM`	Number of results (default: 5, or 20 with --json)
`-c, --collection NAME`	Restrict to specific collection
`--min-score NUM`	Minimum score threshold
`--full`	Return complete document content in results
`--all`	Return all matches

Retrieval Commands

get (single document)

qmd get docs/guide.md --json
qmd get "#a1b2c3" --json
qmd get notes/meeting.md:50 -l 100 --json

multi-get (multiple documents)

qmd multi-get "docs/*.md" --json
qmd multi-get "api.md, guide.md, #abc123" --json
qmd multi-get "notes/**/*.md" --json --max-bytes 20480

Maintenance Commands

qmd update              # Re-index changed files
qmd status              # Check index health
qmd collection list     # List all collections

Search Mode Selection

Mode	Speed	Quality	Best For
search	Fast	Good	Exact keywords, known terms
vsearch	Medium	Better	Conceptual queries, synonyms
query	Slow	Best	Complex questions, uncertain terms

Performance note: vsearch and query have ~1 minute cold start latency for vector initialization. Prefer search for interactive use.

MCP Server

qmd can run as an MCP server for direct integration:

qmd mcp

Exposes tools: qmd_search, qmd_vsearch, qmd_query, qmd_get, qmd_multi_get, qmd_status

---name: qmddescription: Search and retrieve markdown documents from local knowledge bases using qmd. Supports BM25 keyword search, vector semantic search, and hybrid search with LLM re-ranking. Use for querying indexed notes, documentation, meeting transcripts, and any markdown-based knowledge. Requires qmd CLI installed (bun install -g https://github.com/tobi/qmd).---# QMD - Local Markdown SearchSearch and retrieve documents from locally indexed markdown knowledge bases.## Installation```bashbun install -g https://github.com/tobi/qmd```## Setup```bash# Add a collectionqmd collection add ~/notes --name notes --mask "**/*.md"# Generate embeddings (required for vsearch/query)qmd embed```## Usage Rules**Always use `--json` flag** for structured output when invoking qmd commands.## Search Commands### search (BM25 keyword search - fast)```bashqmd search "authentication flow" --jsonqmd search "error handling" --json -n 10qmd search "config" --json -c notes```### vsearch (vector semantic search)```bashqmd vsearch "how does login work" --jsonqmd vsearch "authentication best practices" --json -n 20```### query (hybrid with LLM re-ranking - best quality)```bashqmd query "implementing user auth" --jsonqmd query "deployment process" --json --min-score 0.5```### Search Options| Option | Description ||--------|-------------|| `-n NUM` | Number of results (default: 5, or 20 with --json) || `-c, --collection NAME` | Restrict to specific collection || `--min-score NUM` | Minimum score threshold || `--full` | Return complete document content in results || `--all` | Return all matches |## Retrieval Commands### get (single document)```bashqmd get docs/guide.md --jsonqmd get "#a1b2c3" --jsonqmd get notes/meeting.md:50 -l 100 --json```### multi-get (multiple documents)```bashqmd multi-get "docs/*.md" --jsonqmd multi-get "api.md, guide.md, #abc123" --jsonqmd multi-get "notes/**/*.md" --json --max-bytes 20480```## Maintenance Commands```bashqmd update # Re-index changed filesqmd status # Check index healthqmd collection list # List all collections```## Search Mode Selection| Mode | Speed | Quality | Best For ||------|-------|---------|----------|| search | Fast | Good | Exact keywords, known terms || vsearch | Medium | Better | Conceptual queries, synonyms || query | Slow | Best | Complex questions, uncertain terms |**Performance note:** `vsearch` and `query` have ~1 minute cold start latency for vector initialization. Prefer `search` for interactive use.## MCP Serverqmd can run as an MCP server for direct integration:```bashqmd mcp```Exposes tools: `qmd_search`, `qmd_vsearch`, `qmd_query`, `qmd_get`, `qmd_multi_get`, `qmd_status`

Frequently asked questions

Qmd