Skill UI

This skill guides the configuration of Speak for enterprise environments, such as schools and large organizations. It covers implementing Role-Based Access Control (RBAC), setting up Single Sign-On (SSO), managing diverse roles (teacher/student), handling class management, and establishing usage reporting. This setup is essential for deploying a secure, scalable language learning platform tailored for institutional use.

This comprehensive guide demonstrates how to build a robust AI language tutoring session using the Speak SDK. It covers initiating conversations, submitting student responses (text or audio), performing deep pronunciation assessment at the phoneme level, and generating detailed session summaries with grammar and vocabulary metrics. Ideal for developing language education platforms and testing API integration.

Provides a comprehensive incident response runbook for managing outages of the Speak API. It covers critical procedures including API triage, implementing offline fallback modes, and ensuring robust recovery steps. Ideal for DevOps teams maintaining language learning platforms reliant on real-time AI services (GPT-4o, Whisper).

This guide details how to set up the Speak language learning platform integration. It covers installing necessary SDKs (Speak SDK, OpenAI), configuring API keys, and establishing the connection required for sophisticated AI-powered tutoring. Use this when building applications that require real-time speech recognition, pronunciation feedback, and multilingual language support.

A comprehensive guide and setup for building a fast, reliable local development workflow for language learning applications. It includes setting up mock tutor responses for offline testing, generating audio test fixtures using TTS, and implementing a debug mode for detailed pronunciation scoring analysis. Ideal for engineers setting up a new Speak-based integration or refining existing test pipelines.

This guide provides a comprehensive deep dive for migrating language learning platforms, covering everything from importing student progress to transitioning from legacy speech APIs. It details configuration using modern SDKs, integrating services like OpenAI's GPT-4o and Whisper, and includes verification steps. It is essential for managing complex platform migrations and ensuring a smooth operational transition.

This guide details how to configure the Speak language learning platform across multiple environments (dev, staging, production). It is essential for implementing robust SaaS deployments, ensuring that separate API keys, mock modes, and environment variables are correctly managed for seamless development and operational management.

This skill provides comprehensive observability for the Speak language learning platform. It monitors critical metrics such as API health status, assessment latency, session usage, and detailed pronunciation score distributions. It is essential for developers implementing robust, production-grade monitoring systems and managing large-scale language learning operations.

This guide provides a comprehensive method for optimizing the latency and reliability of the Speak API integration. It covers techniques such as audio preprocessing, implementing response caching, and managing connection pooling. Use this skill when establishing a production-grade, low-latency language learning platform or managing high-volume API operations.

This guide provides robust patterns for managing external API rate limits, specifically detailing the implementation of exponential backoff, request queuing, and throttling strategies. It uses TypeScript examples to ensure stable and reliable API interactions. Use this when building production-grade applications that require frequent, high-volume calls to rate-limited services, such as language learning APIs.

This guide provides the complete, production-grade reference architecture for integrating the Speak language learning platform. It covers all necessary components, including the client, API gateway, assessment engine, and progress store. Use this blueprint to ensure a robust, scalable, and reliable implementation for managing large-scale language learning operations.

This guide provides production-ready patterns for integrating the Speak language learning API. It covers managing conversation sessions, performing pronunciation assessment, preprocessing audio files using ffmpeg, implementing robust retry mechanisms (with backoff), and tracking user learning progress. Use this when developing a full-featured, high-reliability language learning application or troubleshooting complex API integrations.