Agent skill · bighardperson
qmd
Local hybrid search for markdown notes and docs. Use when searching notes, finding related content, or retrieving documents from indexed collections.
What it needs
About 3k tokens when loaded.
What this skill does
qmd - Quick Markdown Search Local search engine for Markdown notes, docs, and knowledge bases. Index once, search fast. When to use (trigger phrases) "search my notes / docs / knowledge base" "find related notes" "retrieve a markdown document from my collection" "search local markdown files" Default behavior (important) Prefer qmd search (BM25). It's typically instant and should be the default. Use qmd vsearch only when keyword search fails and you need semantic similarity (can be very slow on a cold start). Avoid qmd query unless the user explicitly wants the highest quality hybrid results and can tolerate long runtimes/timeouts. Prerequisites Bun >= 1.0.0 macOS: brew install sqlite (SQLite extensions) Ensure PATH includes: $HOME/.bun/bin Install Bun (macOS): brew install oven-sh/bun/bun Install bun install -g https://github.com/tobi/qmd Setup What it indexes Intended for Markdown collections (commonly /.md). In our testing, "messy" Markdown is fine: chunking is content-based (roughly a few hundred tokens per chunk), not strict heading/structure based. Not a replacement for code search; use code search tools for repositories/source trees. Search modes qmd search (default): fast keyword match (BM25) qmd vsearch (last resort): semantic similarity (vector). Often slow due to local LLM work before the vector lookup. qmd query (generally skip): hybrid search + LLM reranking. Often slower than vsearch and may timeout. Performance notes qmd search is typically instant. qmd vsearch can be ~1 minute on some machines because query expansion may load a local model (e.g., Qwen3-1.7B) into memory per run; the vector lookup itself is usually fast. qmd query adds LLM reranking on top of vsearch, so it can be even slower and less reliable for interactive use. If you need repeated semantic searches, consider keeping the process/model warm (e.g., a long-lived qmd/MCP server mode if available in your setup) rather than invoking a cold-start LLM each time. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
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