Skill UI

This SDK enables developers to build robust content moderation applications in Java using the Azure AI Content Safety services. It provides comprehensive capabilities to analyze both text and images for harmful content, detecting categories such as hate speech, violence, and sexual material. Furthermore, the SDK allows for custom blocklist management, enabling users to filter specific undesirable keywords or phrases to ensure strict content compliance and safety across various enterprise applications.

This SDK enables developers to build robust content moderation applications in Java using the Azure AI Content Safety services. It provides comprehensive capabilities to analyze both text and images for harmful content, detecting categories such as hate speech, violence, and sexual material. Furthermore, the SDK allows for custom blocklist management, enabling users to filter specific undesirable keywords or phrases to ensure strict content compliance and safety across various enterprise applications.

This SDK provides a comprehensive interface for building real-time, bidirectional voice AI applications using Azure AI services. It supports streaming audio input/output via WebSocket, handling transcription, text-to-speech, and complex session management. Ideal for developing robust voice assistants and interactive AI agents in both Node.js and modern browser environments.

This skill provides implementation patterns for cost tuning within the Retell AI platform, specifically tailored for voice agents and complex telephony workflows. It helps developers build, monitor, and optimize the operational costs of AI-powered voice automation systems, ensuring efficient resource management when integrating real-time voice services.

A comprehensive expert for deploying and scaling AI agents using AWS Bedrock AgentCore. This guide covers the full lifecycle of agent management, including service selection (Gateway, Runtime, Memory, Identity, etc.), deployment patterns, credential management, and advanced integration workflows required for enterprise-scale AI solutions.

A comprehensive guide to production-ready patterns for ElevenLabs' TypeScript and Python SDKs. This resource covers crucial best practices including singleton client implementation, type-safe TTS service wrappers, robust error classification (rate limiting, quota), and concurrency management using request queues. Essential for building scalable and reliable voice AI applications.

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

This skill provides the central management layer for defining an AI agent's capabilities. It uses the `capabilities.yaml` file as the single source of truth to configure everything from integrated skills, tools, hooks, and sub-agents. Use this when running any `capa` command (install, clean, add, etc.), integrating a new service, or troubleshooting the project's entire operational environment.