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Convert documents and files to Markdown using markitdown. Use when converting PDF, Word (.docx), PowerPoint (.pptx), Excel (.xlsx, .xls), HTML, CSV, JSON, XML, images (with EXIF/OCR), audio (with transcription), ZIP archives, YouTube URLs, or EPubs to Markdown format for LLM processing or text analysis.
Expert in parsing bank statement PDFs using Docling, handling duplicate transaction detection, and validating against bank summaries. Use when working with bank statement imports, transaction parsing, or financial data validation.
Multi-format document parsing tools for PDF, DOCX, HTML, and Markdown with support for LlamaParse, Unstructured.io, PyPDF2, PDFPlumber, and python-docx. Use when parsing documents, extracting text from PDFs, processing Word documents, converting HTML to text, extracting tables from documents, building RAG pipelines, chunking documents, or when user mentions document parsing, PDF extraction, DOCX processing, table extraction, OCR, LlamaParse, Unstructured.io, or document ingestion.
將文字或 Markdown 報告轉換為 PDF、Word (DOCX) 或 Markdown 檔案。
Create, improve, and debug professional LuaLaTeX documents using KOMA-Script + the moderndoc package (and the legacy modern-doc shim). Use for: generating new documents from a goal, improving typography/layout, producing PDF/A-4-friendly output, setting up minted/biblatex/tabularray/tikz, converting Mermaid → TikZ, and debugging compilation logs.
Transcribe handwritten book notes from reMarkable PDFs or paper photos. Trigger phrase "process book notes". Handles single-source book notes with optional chapter structure. Converts handwriting to markdown, applies formatting conventions, generates metadata, creates AI summaries, and appends quotes to a central quotes file. Notes may be in Czech or English.
Analyzes before/after architectural and structural plan PDFs to identify engineering changes, focusing on framing and hardware modifications. Use when users need to compare plan revisions, identify changes before creating BOMs, validate ECIR line items against plans, document visual evidence of engineering changes, or train estimators on plan-to-cost relationships. Handles 20-30 page residential plans (architectural/structural sheets only).
PDF export implementation patterns using html2pdf.js with iframe isolation
Reads PDF files and extracts text content in Markdown format. Handles tables and multi-page documents. Use when needing to read PDF documents. Requires pdfplumber package.
Enables Claude to read, manipulate, and fill out PDF forms
Convert documents (PPTX, PDF, DOCX, XLSX, images) to Markdown/JSON/HTML using IBM Docling. This skill should be used when user asks to convert, parse, or extract content from documents. Triggers on "convert pptx", "parse pdf", "extract from document", "конвертуй презентацію", "витягни з pdf".
Expert knowledge for creating effective cheat sheets with PDF export. Activate when creating/editing cheat sheet content, designing quick reference sheets, or working with PDF export functionality. (project)
Convert entire PDF documents to clean, structured Markdown for full context loading. Use this skill when the user wants to extract ALL text from a PDF into context (not grep/search), when discussing or analyzing PDF content in full, when the user mentions "load the whole PDF", "bring the PDF into context", "read the entire PDF", or when partial extraction/grepping would miss important context. This is the preferred method for PDF text extraction over page-by-page or grep approaches.
Extracts all chunks with three-tier contextual embeddings from a specific PDF file in Qdrant vector database and saves to plain text. Use when user wants to extract, export, dump, or view all chunks from a PDF document, inspect file content, save chunks for analysis, or review contextual embeddings.
Create and edit Excel spreadsheets (.xlsx) in Python with openpyxl/xlsxwriter. WHEN: Creating Excel files with formulas/formatting, reading .xlsx/.xlsm files, modifying spreadsheets while preserving formulas, adding charts/visualizations to Excel. WHEN NOT: Simple CSV reading (use pandas), Word documents (use python-docx), PDF files (use python-pdf).
Run the complete PDF processing pipeline to convert the manual PDF into Next.js application data. This command executes all steps automatically: split, render, extract, translate, build, and manifest.
Process and transform FAQ documents (xlsx, word, pdf, txt) into RAG-optimized format. Use when working with FAQ files, knowledge base documents, or when the user needs to analyze and restructure FAQ content for RAG systems.
