Skill UI

This integration provides programmatic access to Runway's powerful AI creative platform. Use it for advanced tasks such as generating high-definition videos from text prompts, performing image-to-video transformations, or applying complex creative AI filters. It is essential for developers building applications that require cinematic, generative media capabilities.

This guide provides a comprehensive workflow for generating cinematic AI videos using Runway's Gen-3 Alpha model via the Python SDK. It covers the entire process from text-to-video task creation, polling for task completion status, to successfully downloading the final high-quality video output. Ideal for developers integrating advanced creative video generation into their applications.

This skill provides a development loop for RunwayML, an advanced creative AI platform. It allows users to programmatically generate high-quality videos from images or text prompts using the Python SDK. Ideal for integrating Runway's capabilities into local development workflows, enabling advanced creative video production, editing, and media manipulation.

This skill provides the implementation pattern and comprehensive guide for integrating the Runway ML API. It demonstrates using the Python SDK to perform advanced creative tasks, such as image-to-video generation. Furthermore, it includes crucial error handling instructions for managing common issues like API rate limits, unauthorized access (401), and credit exhaustion.

This skill provides implementation patterns for using the Runway SDK. It enables users to perform advanced creative AI tasks, such as generating videos from text prompts or converting images to video, using the official Python SDK. It covers the full workflow, including setup, task execution, output retrieval, and error handling, making it ideal for creative media automation and advanced video production workflows.

This skill provides comprehensive integration patterns for the RunwayML platform, specializing in advanced AI video and image generation. Developers can programmatically create high-quality video content from text prompts or images, supporting sophisticated creative workflows. It is essential for building applications that require programmatic access to industry-leading creative AI capabilities.

This skill provides implementation patterns for interacting with RunwayML webhooks. It enables complex tasks such as AI video generation, image editing, and advanced creative content workflows. By using the provided Python SDK pattern, developers can trigger video creation tasks (e.g., image-to-video) and handle the asynchronous results, making it ideal for integrating high-end creative AI into applications.

An advanced AI tool utilizing Meta's Segment Anything 2 (SAM2) model for interactive, pixel-perfect object segmentation. Users can click on any object within a frame or video to automatically generate precise masks. Key features include point/box prompting, video tracking across multiple frames, and seamless integration into Annotation Studio workflows, making it ideal for large-scale data labeling and video analysis pipelines.

This skill provides comprehensive diagnosis and optimization for agent skill libraries. By analyzing historical session transcripts from platforms like Claude Code and Codex, alongside static skill file checks, it scores each skill across 8 dimensions. It identifies issues such as low trigger rates, poor post-invocation user reaction, and incomplete workflow execution, generating a prioritized report (P0/P1/P2) to significantly improve the agent's overall performance and reliability.

This comprehensive benchmark suite evaluates the performance of Vision-Language Models (VLM) on complex video anomaly detection tasks using the SmartHome-Bench dataset. It covers a wide range of real-world smart home scenarios, including security breaches, elderly fall detection, and unusual pet behavior. Unlike single-frame analysis, this benchmark requires deep multi-frame video understanding, making it a robust tool for testing the advanced AI capabilities of video monitoring systems.

A comprehensive guide to optimizing operating costs when utilizing Together AI's OpenAI-compatible API. This resource details strategies for cost reduction across various AI tasks, including inference, fine-tuning, and model deployment. Learn how to select appropriate model sizes, implement caching, leverage batch inference, and utilize Turbo variants to maximize efficiency and minimize spending.

This debug bundle provides comprehensive guidance for working with Together AI's OpenAI-compatible API. It supports critical LLM lifecycle tasks, including inference, fine-tuning, and model deployment for over 100 open-source models (e.g., Llama, Mixtral). It also includes detailed troubleshooting steps and solutions for common API errors (like 401 Unauthorized or 429 Rate limit), ensuring smooth development.