Skill UI

OpenRouter provides a unified API gateway to access leading AI models (OpenAI, Anthropic, Google, Meta, etc.) from a single endpoint. This skill is essential for developers who need to compare model performance (latency, tokens) across different providers, build resilient cross-provider fallback workflows, or manage complex AI pipelines without writing provider-specific code. It supports feature normalization and BYOK (Bring Your Own Key) for high-volume production use.

This skill guides developers on migrating their codebase from direct OpenAI API calls to using OpenRouter. By making minimal changes—primarily updating the base URL and API key—users gain access to over 400 models from multiple providers (including Anthropic and Google) through a unified SDK interface, ensuring high compatibility and flexible model switching.

This advanced tool simulates complex DeFi flash loan strategies across major protocols like Aave, dYdX, and Balancer. It calculates net profitability, estimates gas costs, and assesses comprehensive risks (MEV, liquidity, execution). Use it to evaluate arbitrage opportunities, analyze liquidation potential, or compare multiple lending providers before executing real transactions.

A comprehensive development tool for building and managing enterprise-grade transactional email systems. It supports modern React Email and MJML templates, generating production-ready code for major providers like Resend, Postmark, and SendGrid. Key features include multi-provider integration, internationalization (i18n), dark mode, spam score optimization, and advanced analytics tracking. Ideal for setting up new products or migrating legacy email infrastructure.

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

This blueprint guides the creation of F.R.I.D.A.Y., a tactical, low-latency voice assistant inspired by Iron Man. It utilizes the specialized Pipecat framework to orchestrate a comprehensive, real-time audio pipeline: STT (OpenAI Whisper/GPT-4o) -> LLM (Gemini) -> TTS (OpenAI Nova). Ideal for developers needing to build advanced, multi-provider, conversational voice applications.

Implement Okta as a centralized Identity Provider (IdP) for robust multi-cloud security across AWS, Azure, and GCP. This skill covers configuring Single Sign-On (SSO), deploying phishing-resistant Multi-Factor Authentication (MFA), automating user lifecycle management via SCIM, and enforcing adaptive access policies based on device posture and user risk, helping organizations achieve Zero Trust compliance.

PydanticAI is a robust Python framework that integrates Pydantic's type-checking and validation capabilities into Large Language Models (LLMs). It allows developers to build production-ready AI agents that guarantee structured, validated outputs, moving beyond simple raw strings. Key features include supported tool calling, dependency injection for testability, and multi-model compatibility across major providers like OpenAI, Anthropic, and Gemini. Use this when reliability and correct data structure are paramount.

This comprehensive guide details the correct usage of the Flutter `provider` package, a widely adopted state management solution. It covers various provider types, including `ChangeNotifierProvider`, `FutureProvider`, and `StreamProvider`. Learn best practices for setting up state with `MultiProvider` and mastering state consumption techniques like `context.watch`, `context.read`, and `Selector`, ensuring efficient and type-safe application development.

This skill guides the integration of Arize AX tracing into existing applications, especially complex LLM applications. It follows a structured, two-phase, agent-assisted flow: first analyzing the codebase (read-only) to understand dependencies, and then implementing instrumentation. It supports multi-language environments (Python, TypeScript, Java, Go) and integrates deeply with OpenTelemetry and various LLM providers, ensuring comprehensive observability without altering core business logic.

Self-hosted open-source alternative to Google NotebookLM. Organize research sources, generate AI notes and summaries, create multi-speaker podcasts, chat with documents, and search materials via full-text or vector search with 16+ AI providers.

Automates comprehensive regression testing for all enabled cloud Large Language Model (LLM) providers. This includes verifying core connectivity, standard chat completion, structured JSON output, and Server-Sent Events (SSE) streaming capabilities. Essential for ensuring the reliability and stability of multi-cloud AI integrations in a CI/CD pipeline.