Search an indexed knowledge base with natural language and return semantically ranked results.
npx skills add https://github.com/robwestz/memoryporter --skill kb-query-robwestz
Please help me install this Agent Skill. Skill: kb-query Source: https://github.com/robwestz/memoryporter/tree/main/skills/skill-kb-query Command: npx skills add https://github.com/robwestz/memoryporter --skill kb-query-robwestz
KB-Query addresses the challenge of finding relevant information within vast knowledge bases, providing efficient and attributed search results.
Ask the KB about session tools using the command: "Ask my devin-docs KB about session tools".
High-intent search queries and answers about installing and using this skill.
Semantic search finds relevant information within indexed knowledge bases by ranking results based on semantic relevance. It delivers relevant chunks from the knowledge base and ensures all retrieved information is attributed to its original source.
The best way to search indexed documents with source attribution is to use natural language querying. This approach retrieves relevant chunks ranked by semantic relevance while ensuring all information is attributed to its original source for integrity.
Yes, you need the kb-forge-cli dependency to perform semantic search on a knowledge base. This dependency provides the necessary environment setup tools and outputs required to index and query the knowledge base effectively.
Semantic search works for information retrieval by processing natural language queries against an indexed knowledge base. It evaluates semantic relevance to rank and return the most relevant chunks of information, providing accurate results with source attribution.
qodex-aiBuild chat interfaces for natural language document querying.
thecloudtipsSynthesize sourced answers with inline citations and confidence ratings.
RigohlCoordinate hybrid semantic and full-text search across multiple engines via FFI.
zilliztechCombine BM25 keyword matching with vector semantic similarity in Milvus.
