Skill UI

This skill provides expertise in building production-grade, scalable data systems and pipelines. It covers the full spectrum of data engineering, including designing robust batch ETL/ELT workflows, implementing real-time streaming architectures (Kafka/Flink), and utilizing modern tools like Airflow, Spark, and dbt. Essential for data architecture design, data lakehouse implementation, and data governance.

Guides you through React Server Components in Next.js App Router, covering when to use server versus client pieces, interop boundaries, data fetching patterns, streaming with Suspense, and composition techniques such as client wrappers or slot-based shells for mixed trees.

Automates spark job creation within data pipelines by guiding etl, transformation, orchestration, and streaming workflows; includes industry best practices, code templates, and validation to deliver production-ready jobs.

Automates Spark SQL optimizer tasks in data pipelines by guiding best practices, producing production-ready code and configurations, and validating ETL, transformation, orchestration, and streaming workflows.

Automated guidance for SQL transform helper tasks within data pipelines, covering ETL, data transformation, workflow orchestration, and streaming, while following best practices, generating production-ready code, and validating results.

Automates guidance for streaming inference setup, covering best practices in ML deployment, serving, monitoring, and production-ready configurations whenever you ask about streaming inference patterns or implementation.

Guides building async worker pipelines for real-time conversational voice agents with streaming transcription, LLM reasoning, and interrupt-aware TTS across providers.

OpenAI’s Whisper provides robust multilingual speech-to-text transcriptions, translations to English, and language detection across 99 languages, suitable for podcasts, meetings, and noisy audio workflows with CPU/GPU acceleration and batch or streaming modes.

Direct REST API access to UniProt for searching proteins, fetching FASTA sequences, mapping identifiers, selecting annotations, and streaming large datasets within Python workflows.

This comprehensive skill provides an end-to-end solution for video and audio content creation. Users can upload videos from various sources (YouTube, local files) and perform advanced operations such as real-time streaming, semantic search, and complex editing (trimming, overlays). Key features include AI-powered transcription, subtitle generation, and the ability to generate diverse media assets like images, music, sound effects, and voiceovers, making it ideal for content creators and media professionals.

This comprehensive guide provides step-by-step instructions for integrating the Google Gemini API into applications using Python and Node.js. It covers the entire lifecycle, from basic text generation to advanced use cases like multimodal inputs (text + image), real-time streaming responses, function calling/tool use, and multi-turn chat. Includes best practices for model selection, error handling, and production deployment.

MolyKit is a comprehensive toolkit designed for building robust, cross-platform AI chat applications. It provides core utilities for integrating large language models (LLMs) like OpenAI, handling real-time SSE streaming responses, and managing complex cross-platform asynchronous patterns (PlatformSend, spawn()). The kit includes ready-to-use widgets for messages, prompt inputs, and avatars, making it ideal for developers creating sophisticated, multilingual chat experiences.