Total 30,580 skills, Document Processing has 447 skills
Showing 12 of 447 skills
Automatically add [[wikilinks]] to all mentions of existing entities within a file or entire world. Scans for entity names, aliases, and partial matches, then wraps them in wikilink syntax. Use when user wants to "linkify", "auto-link", "add links to existing entities", or "wikilink this file".
This skill should be used when the user asks to review, proofread, check, or evaluate content. It provides comprehensive text review (grammar, logic, compliance) and version evaluation (A/B testing, comparison analysis). Text review automatically adds AI disclaimer at the end.
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction. Originally from OpenAI's curated skills catalog.
Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks. Originally from OpenAI's curated skills catalog.
Python library for programmatic PDF generation and creation. Use when user wants to generate PDFs from scratch, create invoices, reports, certificates, labels, or custom documents with precise control over layout, fonts, graphics, tables, and charts. Supports both low-level drawing (Canvas) and high-level documents (Platypus).
Creation, editing, and analysis of Word documents, supporting track changes, comments, format retention, and text extraction. Use this when you need to create .docx files, modify content, handle track changes/comments, or perform other document tasks.
Read Codex logs for this repo and synthesize docs in docs/.
Optimizes markdown documents for token efficiency, clarity, and LLM consumption. Use when (1) a markdown file needs streamlining for use as LLM context, (2) reducing token count in documentation without losing meaning, (3) converting verbose docs into concise reference material, (4) improving structure and scannability of markdown files, or (5) preparing best-practices or knowledge docs for agent consumption.
Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI, token efficiency, verbose markdown, reduce file size
Scan and catalog document collections with metadata extraction, categorization, and statistics. Use for auditing document libraries, preparing for knowledge base creation, or understanding large file collections.
Comprehensive Word document toolkit for reading, creating, and editing .docx files. Supports text extraction, document creation with python-docx, and tracked changes via redlining workflow. Use for legal, academic, or professional document manipulation.
Coding assistance for [GemBox components](https://www.gemboxsoftware.com/). Use when users ask about any GemBox component or coding task that can be performed with a GemBox component. This includes GemBox.Spreadsheet (.NET read/write Excel files), GemBox.Document (.NET read/write Word files), GemBox.Pdf (.NET read/write PDF files), GemBox.Presentation (.NET read/write PowerPoint files), GemBox.Email (.NET read/write email files, send/receive emails), GemBox.Imaging (.NET read/write image files), and GemBox.PdfViewer (JavaScript display/print/save PDF files).