Skill UI

A comprehensive skill for creating, editing, and automating complex spreadsheet workflows using LibreOffice Calc. This includes generating new ODS files, performing format conversions (XLSX, CSV, PDF, etc.), executing advanced formulas, and automating data processing through Python scripting (UNO, ezodf) or command-line interfaces. Ideal for data analysis, reporting, and batch processing tasks.

This skill automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

This skill provides a comprehensive workflow for building vendor-agnostic detection rules using the Sigma format. It empowers security operations center (SOC) engineers to translate raw threat intelligence and MITRE ATT&CK techniques into standardized, portable detection logic. The process guides users through rule validation and conversion into specific queries for major SIEM platforms, including Splunk, Elastic, and Microsoft Sentinel, ensuring robust detection coverage.

Use terminal commands to discover, list, create, edit, move, copy, enable/disable, and delete AI agent skills across 11 tools, handling format conversions and scope overrides between global and project configurations.

Use terminal commands to discover, list, create, edit, move, copy, enable/disable, and delete AI agent skills across 11 tools, handling format conversions and scope overrides between global and project configurations.

This skill provides the comprehensive reference architecture and implementation patterns for integrating Runway's advanced AI capabilities. It focuses on guiding developers through the process of AI video generation, image-to-video conversion, and creative content creation using the dedicated Python SDK. Use this when building applications that require high-quality, generative visual media.

This utility provides comprehensive capabilities for viewing, creating, uploading, editing, and comparing Markdown files stored in the cloud drive. It is designed for scenarios requiring local content manipulation, such as creating new files, fetching existing content, performing localized text patching (regex replacement), comparing version differences, or overwriting content. Note that it specifically handles structured Markdown files, not docx conversions, and defers cloud space management operations (like searching, moving, or permissions) to other dedicated skills.

Generates a highly polished, self-contained single-page HTML landing page optimized for maximum conversion. It incorporates advanced features like 3D CSS animations, GSAP scroll effects, and mouse parallax depth. To ensure accuracy, the skill uses a structured intake process (product pitch, target audience, brand colors, and tone) to build a conversion-ready page that reflects the actual product, not generic boilerplate. Outputs a single, deployable HTML file.

This skill serves as a senior QA automation architect to migrate and convert UI test automation scripts between popular frameworks, including Selenium, Playwright, Puppeteer, and Cypress. It handles complex conversions by applying API mapping, lifecycle adjustments, and pattern standardization, allowing users to port tests from one framework to another efficiently.

An expert skill for creating highly optimized, minimal, and fast-starting Windows installers for Python applications. Utilizing advanced techniques like Nuitka's extreme compilation, DLL footprint analysis, and Inno Setup packaging. This process ensures a clean, professional, and resource-efficient deployment, suitable for commercial products, rather than basic script conversion.

This skill acts as a comprehensive map for developing clinical and biomedical NLP pipelines using OpenMed. OpenMed is a local-first Python library that performs named-entity recognition (NER), protected health information (PHI) de-identification, and FHIR export, all running fully on-device without cloud calls. Use this guide when starting a new clinical text project, needing to select the appropriate capability (e.g., zero-shot NER, auditing, or FHIR conversion), or requiring an entry point for the core OpenMed features.

This specialized skill traces the complete lifecycle of an uploaded or imported file through complex backend systems. It maps the sequence from ingress to final consumer, tracking every derived artifact, archive extraction, format conversion, parser invocation, and deserialization step. It is crucial for security analysis, vulnerability research, and understanding how a file reaches a decisive backend effect after initial sandbox assumptions are made.