Index and search local markdown files with hybrid BM25 and vector retrieval.
npx skills add https://github.com/heysuhas/hermes_cli --skill qmd-heysuhas
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/heysuhas/hermes_cli/tree/main/optional-skills/research/qmd Command: npx skills add https://github.com/heysuhas/hermes_cli --skill qmd-heysuhas
This skill solves the challenge of fragmented personal knowledge by providing a high-performance, local-first search engine that indexes your notes, transcripts, and documentation without sending data to the cloud.
Use the qmd skill to perform a hybrid search for information regarding the database migration plan across all indexed collections.
High-intent search queries and answers about installing and using this skill.
This skill enables local markdown search without sending data to the cloud by indexing files locally and executing search queries entirely on your machine. It ensures personal knowledge management remains private and offline.
Hybrid search combines BM25 keyword matching with semantic vector embeddings and LLM reranking to maximize retrieval accuracy. It ensures both exact term matches and contextual meaning are used to locate relevant documents.
Yes, Node.js 22 and local GGUF model execution are required to perform semantic and keyword-based document discovery. These prerequisites enable the local retrieval engine to process your personal notes.
Yes, this skill supports MCP server integration to provide automated agentic retrieval. It connects to the SR Agent as an MCP server to deliver instant, context-aware search results from your knowledge base.
The best way to find decisions in past meeting transcripts is using a local hybrid search engine that indexes transcripts and supports natural language queries. It quickly locates specific information across large local repositories.
projectedanxIndexes and queries local markdown files and transcripts via hybrid BM25, vector embeddings, and LLM reranking search engine.
0xUrsanomicsRetrieve ranked context from local knowledge graphs and memory files.
brittaniebuffiecsuSearch local markdown knowledge bases with hybrid keyword and semantic matching.
Monjyu1101Index and query local knowledge bases with hybrid BM25, vector, and LLM reranking.
