Skill UI

This pattern provides comprehensive guidance for integrating the Wispr Flow voice-to-text API. It covers best practices for both low-latency WebSocket streaming and simpler REST API usage. Key topics include authentication, recommended audio formats, robust error handling, and context awareness (e.g., understanding code or CLI commands), making it ideal for building advanced voice-powered applications.

This guide provides essential security and technical guidance for integrating Wispr Flow's voice-to-text API. It covers best practices for authentication (API keys, access tokens), utilizing streaming methods like WebSockets, handling common API errors, and optimizing context awareness for high-accuracy transcription in various applications.

A comprehensive guide for migrating and integrating with the Wispr Flow voice-to-text API. This skill details best practices for both WebSocket (low-latency streaming) and REST API methods. It covers authentication, optimal audio formatting (16kHz mono PCM), context awareness for specialized jargon (e.g., code), and robust error handling across multiple platforms (Mac, iOS, browser).

A comprehensive guide for integrating the Wispr Flow voice-to-text API using webhooks. This skill covers best practices for real-time speech recognition, including low-latency WebSocket streaming and robust REST API calls. It is essential for developers building voice-powered applications, dictation tools, or any system requiring advanced audio processing and context-aware transcription.

This skill provides a mechanism to execute TypeScript scripts using tsx, enabling fetching and streaming responses from external HTTP endpoints. It is designed for users who need a lightweight Node.js helper utility to manage simple network API calls, making it ideal for rapid integration and data fetching tasks.

This skill provides a robust method for uploading local digital assets, including images, mockups, and full HTML files, to a Stitch project. It bypasses the limitations of standard tool calls by streaming files directly over HTTP, ensuring that large visual assets or complex web pages can be processed accurately for your design and prototyping workflow. Ideal for integrating local design iterations into cloud-based prototypes.

This skill guides developers on building real-time, bidirectional, and multimodal streaming applications using the Gemini Live API. It covers low-latency voice, video, and text streaming over WebSockets, incorporating advanced features like Voice Activity Detection (VAD), function calling, and secure session management. Ideal for conversational AI, interactive video conferencing, and complex real-time user experiences.

Neon Functions provide long-running, stateful, serverless HTTP handlers deployed directly next to your Neon database branch. They are ideal for complex backend workloads that exceed traditional serverless limits, such as real-time WebSockets, Server-Sent Events (SSE) streaming, or sophisticated AI agents. Functions automatically inject the database connection URL and maintain state within the function scope, ensuring high performance and data proximity.

A comprehensive UI component designed to mimic the Spotify Now-Playing interface. It renders current music, podcast, or media content with album art, progress bar, and playback controls. Ideal for video overlays, streaming intros, or personal website hero sections, providing a highly branded and polished look.

This guide details integrating FoundationModels for running Large Language Models (LLMs) directly on the device (iOS 26). It covers advanced patterns including text generation, extracting structured data using @Generable, implementing custom tool calling for domain logic, and streaming responses for real-time UI updates. Key features emphasize strong privacy and offline capability, ensuring no data leaves the device.

A comprehensive guide for optimizing latency-critical systems, such as market data feeds, real-time dashboards, and streaming agents. It details structured methods for mapping 'hot paths,' tracking key metrics (p95, p99 latency, throughput, freshness), and implementing architectural improvements like caching and batching to ensure high performance and data freshness under load.

Uses the Monitor tool to stream real-time events from a swarm system instead of inefficient polling. It provides live observability for key actions like agent spawns, task completions, memory writes, and health status. This is ideal for continuous monitoring and debugging of complex, distributed processes.