documents▌

Add watermarks, page numbers, headers, footers, and other overlay elements to PDF documents.

This skill provides a structured workflow for guiding users through collaborative document creation. Act as an active guide, walking users through three stages: Context Gathering, Refinement & Structure, and Reader Testing.

Complete technical documentation for Hindsight - a biomimetic memory system for AI agents.

Professional document creation, editing, and analysis across Word, PDF, PowerPoint, and Excel formats. \n \n Four specialized sub-skills handle distinct document types: docx for Word documents with tracked changes and comments, pdf for text/table extraction and document merging, pptx for presentation creation and layout management, and xlsx for spreadsheet manipulation and formulas \n Supports both creation from scratch and editing of existing files, with language-specific libraries (docx-js for

Unified cross-application orchestrator for Excel, Word, and PowerPoint document workflows. \n \n Manages application state detection, switching, and document lifecycle (open, save, close) across all three WPS Office applications \n Handles cross-application data migration, content copying, and format synchronization between Excel tables, Word documents, and PowerPoint presentations \n Supports batch operations including format conversion, multi-file processing, and template application across do

XLSX CLI for AI agents. JSON to stdout by default (raw text for --format csv|markdown). Polars+fastexcel for data reads (7-10x faster than openpyxl), openpyxl for metadata/writes, three rendering engines for visual capture (Aspose → Excel → LibreOffice), oletools for VBA.

This skill enables conversion from PDF to editable Word documents using pdf2docx - a Python library that preserves layout, tables, images, and text formatting. Unlike OCR-based solutions, pdf2docx extracts native PDF content for accurate conversion.

Convert PDF files to Markdown with automatic detection of native text vs scanned documents. \n \n Supports three conversion modes: auto-detect (default), native text extraction, and OCR for scanned PDFs \n Fast JavaScript-based processing with no system dependencies; returns JSON output with page count and conversion mode \n Handles basic table structure preservation and works cross-platform on Windows, macOS, and Linux \n OCR for scanned documents requires optional tesseract.js setup; complex m

Handle the request directly. Do NOT spawn sub-agents. Always write the output file the user requests.

Read, create, and edit DOCX files with visual layout validation and professional formatting. \n \n Use python-docx for structured document creation and editing (headings, styles, tables, lists). \n Convert DOCX to PDF to PNG for visual inspection of layout, tables, diagrams, and pagination fidelity before delivery. \n Includes bundled scripts/render_docx.py helper for rendering; falls back to text extraction if visual tools are unavailable. \n Requires python-docx , pdf2image , and system tools