Skill UI

A comprehensive guide detailing how to refactor large, complex SwiftUI views into smaller, more stable, and explicit components. It emphasizes adopting a lightweight state approach (favoring local state and environment variables over excessive view model layers) to improve data flow, readability, and overall code maintainability in modern iOS development.

This skill performs in-depth literature reviews across complex communications domains, including 5G/6G, Wi-Fi, satellite networking, and advanced protocols. It systematically searches user-defined knowledge bases (Zotero, Obsidian, local files) and major academic databases (IEEE, ACM, ScienceDirect) to provide comprehensive survey summaries, related work analyses, and technical landscape overviews.

This skill is designed for running comprehensive evaluations of Hugging Face Hub models on local hardware. It supports multiple evaluation frameworks, including `inspect-ai` and `lighteval`, and provides flexibility in backend selection (e.g., `vllm`, Transformers, or `accelerate`) to optimize for performance and compatibility. Use this for local GPU benchmarking, smoke testing, and backend selection, but note that it does not handle remote job orchestration or result publishing.

This skill provides a managed cloud environment for training and fine-tuning advanced vision models. Users can build and customize models for object detection (e.g., DETR, YOLOS), image classification, and segmentation (SAM/SAM2). By leveraging Hugging Face Jobs, training is executed on powerful cloud GPUs without requiring local GPU setup, and all resulting models are automatically saved to the Hugging Face Hub.

This file serves as a Japanese translation placeholder for the 'product-lens' skill. It indicates that the localization process is currently in progress. Users should refer to the original source file for the complete English version and functionality.

This file serves as a placeholder for the Japanese translation (localization) of the 'project-flow-ops' module. It indicates that the translation is currently in progress. Users should refer to the original English skill file for the core functionality and detailed usage instructions.

Automates the complex pre-development workflow for large-scale system transformations, such as major rewrites, migrations, or overhauls. This skill performs comprehensive project analysis, task decomposition, planning document generation, and sets up detailed progress tracking across multiple phases, ensuring a structured approach before any coding begins. It supports adaptive control and integrates robust task tracking via GitHub or local files.

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.

Utilize Modal, a serverless GPU cloud, for running complex machine learning workloads, including training, fine-tuning, and inference. This tool provides a zero-config environment, eliminating the need for SSH setup or Docker management. It features automatic scale-to-zero billing and local-first execution, making high-powered GPU compute accessible for debugging and small-scale experiments.

This framework manages the ingestion, organization, synchronization, and search of knowledge across multiple storage layers, including local files, persistent memory, vector stores, and Git repositories. It provides a structured approach for ensuring knowledge durability, deduplication, and maintaining a 'single source of truth' across complex development and operational contexts.

This file is dedicated to handling Japanese translations for the 'messages-ops' component. It currently acts as a localization placeholder, indicating that the full Japanese translation is under active implementation. Users should refer to the original English skill file for the core functionality and detailed usage instructions.

This skill file acts as a Japanese translation placeholder for the 'product-capability' module. It indicates that the localized content is currently under development and not functional. Users should refer to the original English skill file for the core functionality and detailed implementation.