Skill UI

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.

A comprehensive checklist designed for developers to ensure a language learning integration (Speak) is robust and ready for production deployment. It covers critical technical areas including API authentication, audio processing pipelines, rate limiting strategies, monitoring and alerting setup, and adherence to global data compliance standards (e.g., GDPR, FERPA). Use this when implementing or troubleshooting production-grade features.

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.

This guide outlines essential security best practices for integrating the Speak API. It covers critical areas like securing API keys using secrets managers, ensuring audio data privacy by deleting local files, and maintaining compliance with major regulations such as COPPA and FERPA. Use this knowledge when building production-ready, secure language learning applications.

This comprehensive guide details the process for upgrading the Speak SDK, migrating data between various language learning platforms (such as Duolingo or Babbel), and handling critical API version deprecations. It provides structured steps for version checking, dependency upgrades, and implementing complex data mapping logic to ensure a smooth transition to production-ready systems.

This skill provides a comprehensive guide for developers to configure and verify webhooks for the Speak language learning platform. It addresses handling critical lifecycle events, including lesson completion, progress tracking, and achievement notifications. Use this when building production-ready integrations or managing enterprise-level data synchronization from Speak's API.

This comprehensive guide assists developers in adopting Test-Driven Development (TDD) practices. It covers generating unit tests for various languages (Python, JS, Java), analyzing test coverage gaps across multiple frameworks (Jest, Pytest, JUnit), and guiding the iterative Red-Green-Refactor workflow. Use this guide when generating stubs, improving test coverage, or adhering to spec-first development methodologies.

Comprehensive TDD workflow guidance covering the Red/Green/Refactor rhythm, Arrange-Act-Assert test structure, Jest/Vitest, pytest, and Go patterns, coverage rules, mocking advice, and anti-pattern warnings to keep teams disciplined across languages.

This skill provides expert guidance on creating, reviewing, and managing production-grade AWS infrastructure using Terraform. It focuses on best practices for reusable module design, robust remote state management (S3 + DynamoDB), and adhering to modern HashiCorp Configuration Language (HCL) patterns like using 'for_each'. Ideal for teams building or auditing complex, scalable AWS environments.