Skill UI

BusyBox is a single, portable binary that implements a vast collection of common Unix utilities (such as ls, grep, sed, etc.). This skill allows users to run standard Unix command-line tools directly within a Windows environment, solving compatibility issues for developers and system administrators who rely on cross-platform scripting. It provides necessary Unix functionality without requiring a full Linux subsystem.

This skill provides comprehensive guidance and established patterns for managing and maintaining Windows 11 operating systems. It is designed to assist users in performing routine system updates, troubleshooting issues, and general system administration tasks within a Windows 11 environment, ensuring system stability and optimal performance.

Provides comprehensive guidance for developing robust, cross-platform Command Line Interface (CLI) applications. Covers the entire workflow from initial UX analysis and command design to implementation using popular frameworks (e.g., commander, click, cobra). Key features include advanced argument parsing, handling shell completions, displaying progress bars, and ensuring reliable terminal interactions across Windows, macOS, and Linux.

A comprehensive guide detailing the installation, setup, and authentication process for Cursor IDE across macOS, Linux, and Windows. It covers account sign-in, plan activation, and the seamless migration of settings and extensions from VS Code, ensuring a fully configured development environment.

This comprehensive guide provides step-by-step instructions for setting up complete development environments from scratch. It covers installing necessary tools (Node.js, Python, Git, Docker), managing dependencies, configuring environment variables, and verifying the entire setup across multiple operating systems (macOS, Linux, Windows). Essential for new project onboarding or machine setup.

A comprehensive guide to diagnosing and resolving common technical issues encountered with the Granola application. Covers fixes for audio capture failures, transcription quality degradation, calendar syncing problems, and integration errors with platforms like Slack and Notion. Includes platform-specific troubleshooting steps for macOS and Windows users.

This comprehensive guide details the end-to-end setup for Granola AI, an advanced AI meeting note-taking solution. It covers initial installation on macOS/Windows, authenticating with major cloud services (Google/Microsoft), and critically, granting all necessary system permissions (Screen Recording, Microphone) to ensure seamless, background audio capture and transcription. Use this guide when setting up Granola for the first time or troubleshooting connectivity issues.

This skill leverages Google Gemini's advanced image generation model to create high-quality, context-specific visuals. It is essential for developers needing placeholder images for UIs, generating detailed diagrams for technical documentation, or visualizing abstract concepts, logos, and assets across cross-platform projects (Windows, macOS, Linux).

Extends transformer context windows using RoPE, YaRN, ALiBi, and position interpolation so long documents (32k-128k+ tokens) can be processed, pre-trained models lengthened, and efficient positional encodings or extrapolation strategies deployed.

Automates designing and implementing table partitioning strategies to keep large databases performant, optimize time-series workloads, and shorten maintenance windows, with guidance on key selection, SQL scripts, and query tuning.

This comprehensive guide provides techniques for acquiring, analyzing, and extracting artifacts from memory dumps. It covers best practices for digital forensics, crucial for incident response and malware analysis. Users learn how to use industry-standard tools like Volatility 3 on Windows, Linux, and macOS, including process, network, and registry deep dives.

This skill provides methodologies for designing sophisticated, layered memory architectures for AI agents. It moves beyond simple context windows and basic vector stores by incorporating short-term, long-term, and graph-based memory systems. Implementing this is crucial for agents that require persistence across sessions, maintaining complex entity consistency, and performing advanced, relationship-driven reasoning over accumulated knowledge bases, including time-aware fact tracking.