Skill UI

A formal framework designed for evaluating AI-assisted code generation sessions. It implements Development Oriented Evals (EDD) principles, allowing users to define capability and regression criteria. The system supports multiple evaluation types—code-based, model-based, and human review—and tracks reliability using advanced metrics like pass@k, ensuring robust quality control for AI agents.

A comprehensive skill for generating multimodal media content using fal.ai models. It supports text-to-image (Nano Banana), text/image-to-video (Veo, Kling, Seedance), and text/video-to-audio (CSM-1B, ThinkSound). Use this tool for any creative project requiring high-quality generated images, videos, or sound effects.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

This expert skill guides the creation of commercial-grade, highly optimized, and professional Windows installers for Python applications. It leverages Nuitka for extreme compilation (LTO, slimming, 32/64-bit selection) and Inno Setup for robust packaging. The goal is to deliver the smallest size, fastest startup time, and a residue-free user experience, strictly avoiding basic single-file builds. Ideal for professional software deployment.

A comprehensive guide to setting up a fast and secure WireGuard VPN server for remote access to your home network (homelab). Learn keypair generation, advanced Linux firewall (iptables) rules, and how to manage different tunneling modes (split vs. full tunnel) for optimal performance.

This tool manages the continuous and periodic execution of specialized background workers, such as security auditing, performance optimization, code mapping, and documentation generation. By utilizing in-session looping (`/loop`) and MCP dispatching, users can schedule critical maintenance tasks (e.g., optimize, audit, consolidate) at fixed intervals, ensuring the system remains monitored and up-to-date.

Manim is a powerful Python library used for creating high-quality mathematical and scientific animations. This skill facilitates the generation of educational videos and complex visualizations for presentations. It is ideal for researchers, educators, or content creators who need to visualize complex concepts in an engaging animated format. Note: This specific file is related to localization/translation.

This skill provides the creative direction layer for video production, focusing on *what* the content should feel like, not just *how* to render frames. It distills complex visual aesthetics (such as angelcore, cloud-trance, or hyperpop) into actionable mood, color palettes, and rhythmic editing grammars. Use it when building music videos, stylistic reels, or guiding AI b-roll generation that must maintain a unified, intentional visual narrative.

This skill intercepts the response flow before generation, allowing the user to explicitly control the desired depth, length, and token usage of the AI's answer. It estimates the complexity of the input prompt and presents multiple options (e.g., 25%, 50%, 75%, 100%), ensuring the output matches the user's need, whether they require a brief summary or a comprehensive, detailed analysis.

This skill provides a comprehensive workflow for training advanced neural network models, including LSTM, Transformer, and N-BEATS, using historical market data. It facilitates model training, prediction generation with confidence intervals, performance comparison across different model types, and the structured storage of results for further analysis and SONA training.

A comprehensive vector search plugin offering two distinct paths: large-scale corpus search using HNSW (supporting RaBitQ quantization for memory efficiency) and a fast WASM-backed router for high-priority hot patterns. Ideal for implementing Retrieval-Augmented Generation (RAG), semantic search across massive datasets, or routing queries to specific, limited patterns.