Search local markdown knowledge bases with hybrid retrieval and reranking.
npx skills add https://github.com/blueskies1818/hermesALIone --skill qmd-blueskies1818
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/blueskies1818/hermesALIone/tree/main/Agent/optional-skills/research/qmd Command: npx skills add https://github.com/blueskies1818/hermesALIone --skill qmd-blueskies1818
This Skill solves the problem of efficiently searching through large collections of markdown notes, documents, and meeting transcripts, providing fast and accurate results without relying on cloud services.
Use the qmd skill to search for information in your local knowledge base using the query 'my research on AI'.
High-intent search queries and answers about installing and using this skill.
You can search local markdown notes without cloud services by indexing them into a personal knowledge base for fast, accurate local retrieval.
Hybrid search for personal knowledge bases combines BM25 keyword matching, vector semantic search, and LLM reranking to provide comprehensive and accurate local search results.
Yes, local knowledge management search requires installing qmd, sqlite, and node, along with associated models, to enable indexing and LLM reranking capabilities.
You index markdown documentation for semantic search by pointing the system at your repository of files, allowing it to process and store the content for vector search and keyword matching.
The best way to retrieve specific information from large markdown collections is using a local hybrid search system that applies BM25, vector search, and LLM reranking to avoid manual sifting.
Use local search for personal knowledge management to keep data private and retrieve information quickly without relying on cloud services, leveraging local models for semantic understanding and reranking.
vikrant-projectIndex markdown notes and transcripts for hybrid local search.
weipingRetrieve relevant references from a personal knowledge base using natural-language queries.
jpjednorskiIndex and search Obsidian vault notes with qmd keyword and semantic queries.
JuanMS20Index Markdown and text files for local hybrid search with BM25, vectors, and reranking.
