Index and search local markdown notes with hybrid retrieval.
npx skills add https://github.com/AlexiosBluffMara/mercury --skill qmd-alexiosbluffmara
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/AlexiosBluffMara/mercury/tree/main/optional-skills/research/qmd Command: npx skills add https://github.com/AlexiosBluffMara/mercury --skill qmd-alexiosbluffmara
Local knowledge is dispersed across notes, docs, and transcripts, making retrieval slow and manual.
Install qmd globally and add a collection to start searching.
High-intent search queries and answers about installing and using this skill.
You can search local markdown notes and transcripts using hybrid retrieval by indexing them locally with qmd, which combines BM25, vector search, and LLM reranking to surface relevant results from your collections.
Hybrid retrieval for local knowledge bases combines BM25 keyword matching, vector embeddings, and LLM reranking to process and surface relevant documents from local collections.
Yes, local knowledge base search requires Node.js 22+ and SQLite with extensions on macOS when needed, alongside local model downloads to function properly.
Yes, MCP integration enables agents like Hermes to use local document search tools directly without repeated skill loading, streamlining retrieval across collections.
The best way to index personal documents for offline search is using a local-first indexing tool that supports offline operation across personal or team knowledge bases.
Limitations of offline search for local markdown collections include requiring local model downloads and specific environment setups like SQLite extensions on macOS to function.
BermudaLocalsSearch local knowledge bases with hybrid BM25, vector, and LLM reranking.
Blake-JohnExport Feishu documents and knowledge-base nodes to Markdown, PDF, or Word.
steipeteIndex local files and search them with BM25, vector, and hybrid queries.
adeboldPerform vector-based semantic search against an AgentDB index.
