Skill UI

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.

Provides comprehensive guidance for optimizing the performance of the Wispr Flow voice-to-text API. This skill covers best practices for integrating dictation, streaming, and building robust voice-powered applications. It details optimal WebSocket usage, recommended audio formats (16kHz PCM), context setting for specialized fields like programming, and robust error handling strategies (e.g., 401 Unauthorized, network disconnects).

This comprehensive checklist provides guidance for integrating the Wispr Flow voice-to-text API into a production environment. It covers best practices for both WebSocket and REST API usage, addressing critical elements like authentication, robust error handling (e.g., 401 Unauthorized or network disconnections), and optimizing performance. It is essential for building reliable, voice-powered applications, especially those handling complex contexts like programming code and CLI commands.

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 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.

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 guides the creation of production-grade Model Context Protocol (MCP) servers and basic clients using C# and the .NET framework. It ensures adherence to the stable 2.x specification, addressing common pitfalls like stateful/stateless HTTP defaults, handling deprecations (roots, sampling), and utilizing appropriate transports (STDIO, Streamable HTTP). Essential for developers integrating structured AI APIs into enterprise applications.

This guide details the architectural and implementation patterns for building modular applications or microservices using the tinystruct Java framework. It covers core concepts like using the @Action annotation for dual routing (CLI/HTTP), managing request state with Context, and using native Builder for JSON serialization, ensuring a lightweight and structured development environment.

Expert skill for building Model Context Protocol (MCP) servers and tools from scratch. Covers the full development lifecycle—from defining tool schemas and resources to implementation, testing, and publishing to registries. Supports robust patterns using TypeScript and Python for integrating custom capabilities into AI agents.

This tool acts as a centralized orchestrator for the entire Go development lifecycle. It analyzes the current task context—whether designing an API, debugging a panic, or building a gRPC service—and intelligently loads multiple, highly relevant skills simultaneously. It ensures developers have comprehensive, context-aware support for complex workflows, handling everything from architecture and error management to performance tuning and security auditing.

A powerful tool for designing and writing deterministic, multi-agent workflow scripts in JavaScript. It allows users to orchestrate complex, repeatable, multi-step tasks using advanced patterns like fan-out, pipelines, loops, and judge-panels. Ideal for automating sophisticated business processes that require multiple specialized sub-agents and robust context management.

This skill provides a comprehensive guide for building scalable Retrieval-Augmented Generation (RAG) pipelines and persistent agent memory using Pinecone as the vector database. It covers index setup, embedding large corpuses, implementing dense and hybrid semantic search, and advanced metadata filtering for real-world production systems. Use this for building searchable knowledge bases and context-aware AI agents.