sear

What problem does it solve?

This Skill eliminates the manual effort and high costs associated with searching vast document collections, building RAG applications, and converting complex file formats like PDFs and DOCX. It provides precise, cited answers, saving you time and money by automating knowledge retrieval and document processing.

Core Features & Use Cases

• Document Conversion: Effortlessly transform PDFs and DOCX files into LLM-optimized markdown, complete with smart OCR for scanned documents.
• Semantic Search & RAG: Index diverse document corpuses (code, docs, research) and perform semantic searches to get LLM-synthesized answers with line-level citations.
• Content Extraction: Retrieve raw, relevant document chunks without LLM generation for focused analysis or further processing.
• Multi-Corpus Management: Organize and search across multiple knowledge bases simultaneously, with clear source attribution.
• Use Case: A legal team can convert hundreds of contracts, index them, and then quickly extract specific clauses or ask complex questions to get cited answers, drastically reducing review time and ensuring compliance.

Quick Start

Convert 'quarterly_report.pdf' to markdown, index it as 'finance_docs', and then search for 'revenue growth projections' within the 'finance_docs' corpus.