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From semantic-search
Indexes a folder of documents for semantic search: scans supported files, extracts text, stores embeddings in local vector database. Reports files indexed, skipped, and errors.
How this command is triggered — by the user, by Claude, or both
Slash command
/semantic-search:index <folder path>The summary Claude sees in its command listing — used to decide when to auto-load this command
Index the specified folder for semantic search. This scans all supported document files, extracts text, and stores embeddings in a local vector database. Call the `index_folder` tool with the provided folder path. Report the results including how many files were indexed, skipped, and any errors encountered.
Index the specified folder for semantic search. This scans all supported document files, extracts text, and stores embeddings in a local vector database.
Call the index_folder tool with the provided folder path. Report the results including
how many files were indexed, skipped, and any errors encountered.
npx claudepluginhub zhubit/cowork-semantic-search/agent-brain-indexIndexes documents and optionally code from a path for semantic and keyword search, creating vector embeddings and BM25 index. Supports incremental updates.
/index-docsIndexes documents from directories, URLs, databases, or APIs into a vector store for retrieval-augmented generation. Supports semantic chunking, embedding generation, and incremental updates.
/indexIndexes the codebase for semantic search, processing files into chunks and embeddings. Supports force rebuild, estimate-only, and verbose flags via arguments.
/pdf-researchIndexes PDFs using LightRAG for semantic search in hybrid/local/global/naive modes, checks index status, and configures directories.
/historianIndexes all files in a directory into a structured concept map with source references, written to input-history.md.
/generate-embeddingsGenerates vector embeddings from text files, database tables, or API responses using models like OpenAI, Cohere, or Sentence-BERT. Stores results in a vector database with metadata and creates a search index.