Agent Skill
2/7/2026qmd
Fast local search for markdown files, notes, and docs using qmd CLI. Combines BM25 full-text search, vector semantic search, and LLM reranking — all running locally. No API keys needed.
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gabrielkoerich
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SKILL.md
| Name | qmd |
| Description | Fast local search for markdown files, notes, and docs using qmd CLI. Combines BM25 full-text search, vector semantic search, and LLM reranking — all running locally. No API keys needed. |
name: qmd description: Fast local search for markdown files, notes, and docs using qmd CLI. Combines BM25 full-text search, vector semantic search, and LLM reranking — all running locally. No API keys needed. homepage: https://github.com/tobi/qmd
qmd - Local Markdown Search
Local search engine for Markdown notes, docs, and knowledge bases. Index once, search fast. Use instead of find for file discovery across large directories.
Installation
bun install -g https://github.com/tobi/qmd
Setup
# Add a collection
qmd collection add /path/to/your/notes --name notes --mask "**/*.md"
# Generate embeddings (required for vsearch/query)
qmd embed
# List your collections
qmd collection list
When to Use
- "search my notes / docs / knowledge base"
- "find related notes"
- "find files matching [pattern]" — use instead of
findto avoid hangs on large directories - "what did we decide about X?"
Default Behavior (important)
- Prefer
qmd search(BM25) — it's instant and should be the default. - Use
qmd vsearchonly when keyword search fails and you need semantic similarity. - Avoid
qmd queryunless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes. - Always use
--jsonflag for structured output when invoking from an agent.
Search Commands
# Fast keyword search (default)
qmd search "authentication flow" --json
qmd search "config" --json -c notes
# Semantic search (slower, for conceptual queries)
qmd vsearch "how does login work" --json
qmd vsearch "best practices for error handling" --json -n 20
# Combined with reranking (best quality, slowest)
qmd query "implementing user auth" --json
qmd query "deployment process" --json --min-score 0.5
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 |
Search Options
| Option | Description |
|---|---|
-n NUM | Number of results (default: 5, 20 with --json) |
-c, --collection | Scope to specific collection |
--min-score NUM | Minimum score threshold |
--full | Return complete document content |
--json | Structured JSON output (agent-friendly) |
--files | File paths only (fast discovery) |
--all | Return all matches |
Retrieve Documents
# Get full file
qmd get docs/guide.md --json
# Get by document hash ID
qmd get "#a1b2c3" --json
# Get specific lines
qmd get notes/meeting.md:50 -l 30 --json
# Get multiple files by glob
qmd multi-get "docs/*.md" --json
qmd multi-get "*.yaml" -l 50 --max-bytes 10240
Output Formats
--files— paths + scores (for file discovery)--json— structured with snippets--md— markdown formatted-n 10— limit results
Maintenance
qmd update # Re-index changed files
qmd status # Check index health
qmd collection list # List all collections
Keeping Index Fresh
# Hourly incremental updates (BM25):
0 * * * * export PATH="$HOME/.bun/bin:$PATH" && qmd update
# Optional: nightly embedding refresh:
0 5 * * * export PATH="$HOME/.bun/bin:$PATH" && qmd embed
MCP Server
qmd can run as an MCP server for direct agent integration:
qmd mcp
Exposes tools: qmd_search, qmd_vsearch, qmd_query, qmd_get, qmd_multi_get, qmd_status
Performance
qmd searchis typically instant.qmd vsearchcan take ~1 minute on first run (loads local LLM).qmd queryadds LLM reranking — can be slow, avoid for interactive use.
Models (auto-downloaded)
All run locally — no API keys needed.
- Embedding: embeddinggemma-300M
- Reranking: qwen3-reranker-0.6b
- Generation: Qwen3-0.6B
- Cache location:
~/.cache/qmd/models/ - Override with
XDG_CACHE_HOMEenvironment variable.
Skills Info
Original Name:qmdAuthor:gabrielkoerich
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