Skill UI

TensorBoard delivers a unified interface to track training metrics, debug network behavior, compare experiments, inspect model graphs, and profile performance for PyTorch or TensorFlow workflows.

Assists with tensorboard visualizer tasks for ML training by guiding setup, best practices, and experiment tracking whenever tensorboard visualization is mentioned, producing production-ready configs and validated outputs.

This guide addresses critical LangGraph streaming pitfalls, including state overdraw, proxy buffering issues (Nginx, Cloud Run), and excessive event noise. It provides a production-grade pattern for implementing robust SSE/WebSocket endpoints using FastAPI. Learn how to correctly select the `stream_mode` (messages, updates, values) and implement server-side event filtering to reliably build live-token chat UIs and perform comprehensive state visualization.

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. It accepts structured English prompts, an optional starting frame image, and style/identity reference images to ensure character and visual continuity. Supports multiple cloud backends (OpenRouter, Volcengine, BytePlus), making it ideal for storyboarding, cinematic concept visualization, or short film pre-production.

A powerful skill utilizing the Google Gemini API to generate high-quality images from text prompts or edit existing photos. It supports various aspect ratios, resolutions (up to 4K), and offers model selection for optimal results, making it ideal for creative design, conceptual visualization, and professional visual content creation.

This skill provides comprehensive strategic guidance for authors targeting ACM SIGGRAPH Asia. It helps assess a computer graphics manuscript's fit, required evidence (visualization, ablations, datasets), and structural positioning to meet the high novelty bar of this flagship venue. Use it for venue selection, manuscript re-framing, and developing a robust submission strategy against close competitors like SIGGRAPH or Eurographics.

This guide provides comprehensive instructions for preparing and submitting supplementary material for computer vision conferences like ECCV. It details how the supplement should support the main paper's claims without adding new results, covering topics such as qualitative result visualization, detailed ablation studies, code archive scrubbing, and ensuring full anonymity across all uploaded assets.

This skill constructs a comprehensive, chronologically sorted patient timeline from raw clinical entities extracted from medical notes. It specializes in temporal normalization, resolving both absolute and relative dates (e.g., 'two days after admission') against a defined anchor date. The resulting sorted sequence of diagnoses, medications, and procedures is ready for immediate visualization or seamless export to FHIR resources.

Compile documents, notes, transcripts, research materials, or code repositories into an evidence-grounded, visualization-ready knowledge graph with typed entity nodes, statement-level provenance, and directed relationship edges.