Skill UI

This guide outlines the end-to-end process for deploying Speak language learning features to modern cloud environments, including Vercel, Cloud Run, or containerized setups. It covers initial configuration, implementing the core logic using TypeScript, and performing production verification. Use this skill when setting up a new Speak integration in a production environment or managing the platform's deployment lifecycle.

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.

A placeholder skill definition that outlines where to insert a descriptive summary and usage guidance so Claude knows when to call this template.

Document outlines testing strategies such as contract, snapshot, mutation, property-based, integration with containers, and disciplined test organization to help teams design reliable suites that cover behavior, API contracts, and invariants.

Automatically guides the creation of technical-doc tutorial outlines, covering API docs, user guides, architecture docs, and documentation automation with best practices, production-ready outputs, and validation when you mention “tutorial outline creator”.

This comprehensive guide outlines the production-grade reference architecture for advanced AI meeting systems using TwinMind. It details the end-to-end workflow, integrating high-accuracy transcription (Ear-3), AI summarization (GPT-4, Claude, Gemini), memory vault management, and automatic action item and calendar integration. Use this resource when implementing or managing a robust, automated AI meeting solution.

This skill outlines security best practices for the TwinMind AI meeting assistant. It covers crucial aspects like on-device audio processing, encrypted cloud backups, and managing microphone permissions. Use it when setting up new TwinMind instances or managing AI operations to ensure data privacy, compliance, and robust security for sensitive meeting data.

This comprehensive guide outlines security best practices for utilizing Vast.ai's cloud environment. It covers secure API key management, hardening SSH access to GPU instances, implementing proper data cleanup before instance destruction, and adhering to robust network security protocols. Use this when setting up, auditing, or deploying sensitive AI/ML workloads on shared cloud hardware.

This comprehensive guide outlines best practices for optimizing vector indexes for production systems. It covers critical techniques such as tuning HNSW parameters, implementing quantization strategies, and optimizing memory usage. Use this when you need to balance search latency, recall, and scalability for large-scale vector databases.

This comprehensive guide outlines the core principles for developing immersive Virtual and Augmented Reality (VR/AR) applications. It covers critical aspects such as platform selection (Quest, ARKit, ARCore), mandatory performance metrics (FPS, frame budget), user comfort techniques (motion sickness prevention), and best practices for spatial interaction and world design. Essential reading for engineers building next-generation spatial computing experiences.

This skill provides comprehensive guidance on selecting the optimal workspace architecture for Windsurf, adapting to various project scales. Whether managing small solo projects, large monorepos, or complex multi-service, polyglot systems, it outlines strategies for structuring file systems and configuring rules. The goal is to ensure that AI tools receive accurate and focused project context, maximizing developer efficiency.

This guide outlines common anti-patterns and critical mistakes when using the Windsurf AI IDE. It covers best practices for prompt engineering, managing workspace scope (especially in monorepos), distinguishing between Supercomplete and Cascade usage, and ensuring safe, maintainable AI-assisted coding workflows. Essential for new developers and team auditors.