Skill UI

This skill automatically detects all available computational resources, including CPU core counts, GPU support (NVIDIA, AMD, Apple Silicon), memory capacity, and disk space. It generates a detailed JSON report that goes beyond simple metrics by providing strategic, context-aware recommendations. These recommendations guide users on the optimal computational approach—such as choosing between Dask for out-of-core processing, selecting the right GPU backend, or determining the ideal number of workers for parallel processing—before running any intensive scientific or data analysis task.

Open Notebook is a powerful, open-source, self-hosted alternative to commercial AI research tools like NotebookLM. It allows users to ingest diverse content (PDFs, videos, web pages) and organize complex research into AI-powered notebooks. Features include context-aware chatting, advanced vector search, multi-speaker podcast generation, and full programmatic access via a REST API, all while ensuring complete data privacy by running on your own infrastructure.

This skill guides AI agents to handle complex technical tasks with maximum precision and minimal computational overhead. It implements adaptive verbosity rules, sophisticated input filtering (for logs, source files, VCS, and payloads), and surgical output generation. It ensures context-window awareness, structured reasoning, and adherence to best practices for coding, debugging, and architecture analysis.

This advanced engine creates deeply personalized, relationship-aware daily gifts using a sophisticated five-stage creative pipeline. It first performs an 'Editorial Judgment' to determine if a gift is warranted, and then generates the content concept. Output can be rendered as interactive H5 web pages, AI-generated images, or videos, ensuring that every artifact is highly unique, contextually relevant, and avoids repetition. Ideal for automated journaling, marking milestones, or maintaining thoughtful daily engagement.

Provides comprehensive guidelines for integrating the Wispr Flow voice-to-text API into development environments. This skill covers both low-latency WebSocket streaming and simpler REST endpoint usage. It is essential for building voice-powered applications, including real-time dictation, command-line interactions, and context-aware code transcription across multiple platforms (Mac, Windows, iOS).

This guide provides detailed instructions for optimizing cost and implementing voice-to-text API integrations using Wispr Flow. It covers best practices for WebSocket streaming, REST API usage, context awareness (like programming code), and robust error handling, helping developers build advanced voice-powered applications.

This technical guide provides comprehensive integration details for the Wispr Flow voice-to-text API. It equips developers with the knowledge to build sophisticated, voice-powered applications. Learn how to utilize WebSocket streaming for low latency or REST endpoints for simple transcription, ensuring accurate context awareness for code and development jargon across multiple platforms.

This guide demonstrates how to integrate Wispr Flow for robust voice-to-text transcription. It covers two primary methods: asynchronous REST calls for transcribing audio files, and real-time WebSocket streaming for live microphone input. Wispr specializes in developer-context-aware dictation, making it ideal for building complex voice-powered applications, especially those involving code or technical jargon.

This comprehensive guide provides developers with best practices and detailed instructions for integrating the Wispr Flow voice-to-text API. It covers critical topics such as managing rate limits, choosing between WebSocket streaming and REST endpoints, handling common error codes (e.g., 401 Unauthorized), and optimizing context awareness, particularly for programming code and developer jargon. Essential for building reliable, low-latency voice-powered applications.

This guide provides the reference architecture and best practices for integrating Wispr Flow's voice-to-text API. It details how to utilize both WebSocket (for low-latency streaming) and REST APIs, covering essential concepts like audio format requirements, context awareness (especially for programming code), and comprehensive error handling strategies.

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.