Skill UI

Provides Python SDK access to Azure Service Bus queues, topics, and subscriptions with async send/receive flows, session-aware routing, scheduled messages, and robust settlement for enterprise messaging scenarios.

Guides researchers through ten structured ideation frameworks to move from vague curiosity to actionable, defensible research proposals, supporting exploration of new problem spaces, pivoting projects, and surfacing high-impact angles.

Provides elite guidance on dynamic context management, vector databases, knowledge graphs, intelligent memory, RAG, and multi-agent workflows so AI systems maintain relevant, actionable information across enterprise scenarios.

Helps teams choose and tune embedding models, chunking, and pipelines for vector search, covering RAG, multilingual input, and dimension-reduction scenarios.

Integrates Apple's FoundationModels into iOS apps so developers can run on-device LLMs for text generation, guided structured outputs via @Generable, custom tool calls, and snapshot streaming without leaving the device.

Guide to reducing Groq inference spend by routing requests to cost-effective models, trimming token usage, caching repeated calls, batching requests, and setting spend limits for Groq Cloud billing scenarios.

Executes Ideogram Core Workflow B, a secondary automation that complements the primary flow by guiding setup, processing, completion steps, collecting API results, and surfacing success or errors in auxiliary scenarios.

Automates inference latency profiler tasks in ML deployment scenarios, offering step-by-step guidance on model serving, MLOps pipelines, monitoring, and production optimization, generating production-ready code and validating outputs against best practices.

llama.cpp is a pure C/C++ library designed for efficient LLM inference, optimized to run on resource-constrained environments. It excels in scenarios where high-end NVIDIA GPUs (CUDA) are unavailable, making it ideal for Apple Silicon Macs, AMD/Intel GPUs, or edge deployment devices like Raspberry Pi. It supports GGUF quantization formats, enabling significant memory reduction and speed improvements for local, cross-platform AI applications.

Executes Retell AI Core Workflow B as a secondary flow that complements the main process, handling setup, processing, completion, and API responses for automation or integration scenarios.

Automates SNS topic configuration tasks within AWS, offering guidance, best practices, code generation, and validation for compute, storage, networking, and serverless scenarios.

Drive Speak's AI-powered conversation practice workflow with real-time pronunciation feedback, grammar guidance, and session summaries for adaptive language tutoring scenarios.