Search markdown knowledge bases with hybrid lex, vector, and HYDE retrieval.
npx skills add https://github.com/jgwill/dotagents --skill qmd-jgwill
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/jgwill/dotagents/tree/main/skills/qmd Command: npx skills add https://github.com/jgwill/dotagents --skill qmd-jgwill
It helps you quickly find relevant information across markdown notes and documentation when you do not know where the answer lives.
Ask qmd to search your markdown knowledge base for “how does the rate limiter handle burst traffic” and return the top relevant results.
High-intent search queries and answers about installing and using this skill.
To search markdown notes, use a hybrid query combining BM25 lex matching, vector semantic search, and HYDE retrieval to find relevant snippets and documents across your knowledge base collections.
Semantic retrieval improves knowledge base discovery by applying vector search and HYDE hypothetical answer generation to find relevant markdown documents even when exact keywords are missing or query intent is ambiguous.
You can filter markdown searches within specific named collections to narrow document discovery, or omit the filter to search across all configured collections in your knowledge base.
An MCP server is not strictly required to query markdown notes; the system also supports a local HTTP mode or the qmd CLI for flexible integration and document retrieval.
The best way to find where a feature is described is running a hybrid search query that combines keyword matching and semantic retrieval to return the most relevant doc sections from your notes.
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