Skill UI

This skill provides high-performance, real-time object detection utilizing the Google Coral Edge TPU accelerator. It processes live camera frames to identify up to 80 COCO classes (e.g., person, car, dog). Optimized for native macOS and Linux deployment, it achieves extremely low latency (e.g., ~4ms at 320x320), making it ideal for embedded vision systems, surveillance, and low-latency monitoring applications.

This skill provides real-time object detection capabilities by leveraging the Google Coral Edge TPU accelerator. It operates natively within Windows Subsystem for Linux (WSL), allowing high-speed, low-latency inference on live camera frames. By utilizing hardware acceleration, it achieves impressive performance (e.g., ~4ms inference at 320x320), making it ideal for edge computing projects requiring rapid visual analysis and resource efficiency.

This skill provides high-performance, real-time object detection using the Intel OpenVINO runtime. It operates via a Docker container, ensuring cross-platform compatibility. Supports detection across various Intel accelerators (NCS2, iGPU, Arc GPU) and CPUs. Users can customize parameters like confidence threshold, target classes, processing FPS, and model precision to optimize performance for specific hardware and accuracy needs.

KubeStellar Console is an open-source, multi-cluster Kubernetes dashboard (CNCF project) that integrates AI-powered operations. It utilizes the kc-agent and MCP server to provide advanced tools for managing Kubernetes environments across edge and cloud. Users can perform AI-assisted troubleshooting, detailed performance testing, root cause analysis (RCA), and monitor over 20 CNCF projects.

A comprehensive audio generation skill designed for professional multimedia content creation. It handles three types of audio output: music (jingles, beds), voiceovers (TTS), and sound effects (SFX). The skill intelligently routes requests to advanced models like Suno V5, Udio, MiniMax TTS, and ElevenLabs, producing a single, high-quality MP3 or WAV file ready for use in marketing, video, or podcast production.

Utilizes Gemini AI to perform broad, comprehensive literature discovery for research papers. Unlike traditional academic APIs (like arXiv or Semantic Scholar), this skill decomposes topics into sub-problems and aliases, ensuring a wider net for finding relevant, cutting-edge academic work across various domains and venues. Ideal for initial research exploration and literature review.

This skill acts as a curated guide and index for AI/ML applications across diverse scientific domains, including biology, chemistry, climate science, and genomics. It helps researchers discover high-signal datasets, state-of-the-art models, and interactive demos hosted on platforms like Hugging Face, allowing for advanced tasks such as drug discovery, protein design, or climate modeling.

A persistent knowledge base that transcends standard RAG by integrating three core layers: raw source storage, a structured knowledge graph, and a dynamic wiki layer. It ingests documents once, automatically extracting entities and relations to build a comprehensive, cross-referenced, and verifiable knowledge graph. Ideal for enterprise research, complex Q&A, and deep knowledge accumulation.

This skill implements advanced 'Gatekeeper' logic to optimize AI agent performance in long-running workflows. It prevents context window bloat by sharding metadata, allocating token budgets, and enforcing Atomic Precision to deliver purely functional, filler-free responses. Ideal for complex coding, multi-step reasoning, and large document analysis where conciseness is critical.