Search markdown repositories using keyword and semantic queries via qmd CLI or MCP server.
npx skills add https://github.com/PlebeiusGaragicus/dot-pi --skill qmd-plebeiusgaragicus
Please help me install this Agent Skill. Skill: qmd Source: https://github.com/PlebeiusGaragicus/dot-pi/tree/main/shared/skills/qmd Command: npx skills add https://github.com/PlebeiusGaragicus/dot-pi --skill qmd-plebeiusgaragicus
It enables quick retrieval of information from markdown knowledge bases, notes, and documentation, reducing the time spent manually searching through files.
Use the qmd skill command to search your markdown notes for the term "API rate limits" and retrieve relevant snippets immediately.
High-intent search queries and answers about installing and using this skill.
To search markdown notes and documentation, you can use keyword and semantic queries to instantly retrieve relevant snippets from your local knowledge base. This skill requires the qmd CLI or MCP server to perform local searches on markdown repositories.
Semantic search for markdown knowledge bases enables fast and accurate information retrieval using vector and hypothetical queries. It indexes your local markdown content to extract relevant knowledge without requiring manual file browsing.
Yes, searching local markdown repositories requires the qmd CLI or MCP server to be installed. These dependencies allow the skill to index and query your local documentation files efficiently.
Yes, you can use vector search to quickly find relevant sections within extensive technical documentation. The skill supports multiple query types including keyword, vector, and hypothetical searches for versatile information extraction.
The best way to retrieve information from a large markdown knowledge base is using a local search engine that indexes markdown content efficiently. This allows you to perform complex keyword and semantic searches to extract relevant references immediately.
Inaccurate markdown search results may occur if the local repository is not properly indexed or if the query type is mismatched. Try utilizing the supported vector or hypothetical search methods instead of basic keyword matching for more relevant knowledge extraction.
tan-yong-shengIndex and query Markdown content locally with keyword and semantic search.
SpaceZephyrPublish Markdown notes to Feishu wiki and read Bitable records.
MrGKanevIndex Markdown notes locally and search via keyword, semantic, or hybrid modes.
channgGenerate static documentation websites from markdown files with sidebar navigation.
