Fast local search for markdown files, notes, and docs using qmd CLI. Use instead of `find` for file discovery. Combines BM25 full-text search, vector semantic search, and LLM reranking—all running locally. Use when searching for files, finding code, locating documentation, or discovering content in indexed collections.
Install
Documentation
qmd — Fast Local Markdown Search
When to Use
- -Finding files — use instead of
findacross large directories (avoids hangs) - -Searching notes/docs — semantic or keyword search in indexed collections
- -Code discovery — find implementations, configs, or patterns
- -Context gathering — pull relevant snippets before answering questions
Quick Reference
Search (most common)
Keyword search (BM25)
qmd search "alpaca API" -c projects
Semantic search (understands meaning)
qmd vsearch "how to implement stop loss"
Combined search with reranking (best quality)
qmd query "trading rules for breakouts"
File paths only (fast discovery)
qmd search "config" --files -c kell
Full document content
qmd search "pattern detection" --full --line-numbers
Collections
List collections
qmd collection list
Add new collection
qmd collection add /path/to/folder --name myproject --mask "*.md,*.py"
Re-index after changes
qmd update
Get Files
Get full file
qmd get myproject/README.md
Get specific lines
qmd get myproject/config.py:50 -l 30
Get multiple files by glob
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
Tips
1. Always use collections (-c name) to scope searches
2. Run qmd update after adding new files
3. Use qmd embed to enable vector search (one-time, takes a few minutes)
4. Prefer qmd search --files over find for large directories
Models (auto-downloaded)
- -Embedding: embeddinggemma-300M
- -Reranking: qwen3-reranker-0.6b
- -Generation: Qwen3-0.6B
All run locally — no API keys needed.
Launch an agent with qmd Search on Termo.