Ingests PDF datasheets or reference manuals into the embedded docs search index via ingest_docs tool. Reports chunks ingested and tables found.
npx claudepluginhub michaelayles/bitwise-mcp --plugin bitwise-embedded-docsThis skill uses the workspace's default tool permissions.
Help the user ingest a PDF documentation file into the embedded docs search index. Use the `ingest_docs` MCP tool with the path to the PDF file.
Indexes PDF documents with LightRAG, extracts text via PyMuPDF, builds embeddings and knowledge graphs, enables hybrid semantic searches with citations for document Q&A.
Searches and navigates PDFs/DOCX/PPTX/Markdown documents, extracts tables/figures, builds wiki knowledge bases using retrieval, deep reading, and ingestion tools.
Implements Google Gemini File Search for managed RAG on 100+ file formats including PDF, code, Markdown. Use for document Q&A, knowledge bases, immutability errors, quotas, polling failures.
Share bugs, ideas, or general feedback.
Help the user ingest a PDF documentation file into the embedded docs search index. Use the ingest_docs MCP tool with the path to the PDF file.
Steps:
ingest_docs with the pathNote: Ingestion may take several minutes for large documents (1000+ pages).