Skill UI

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

Provides comprehensive, enterprise-grade patterns for setting up and managing Veeva Vault across multiple environments. This guide is essential for implementing advanced, compliant deployment strategies in the regulated life sciences sector, covering API usage (VQL, VAPIL) and best practices for data validation and security.

Provides an enterprise-grade framework for managing Webflow access control using OAuth 2.0 and scope-based Role-Based Access Control (RBAC). This system enforces the principle of least privilege by mapping specific user roles (e.g., Viewer, Editor, Admin) to granular Webflow scopes. Key features include per-site token isolation and robust permission checking middleware, significantly enhancing security for complex SaaS integrations.

This API provides a standardized, structured logging abstraction layer for modern application development. It supports multiple log levels (e.g., info, warn, error) and ensures logs are captured in a consistent, machine-readable format. It is essential for building robust applications that require detailed monitoring, debugging, and scalable operational insights.

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 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.

A comprehensive guide for migrating and integrating with the Wispr Flow voice-to-text API. This skill details best practices for both WebSocket (low-latency streaming) and REST API methods. It covers authentication, optimal audio formatting (16kHz mono PCM), context awareness for specialized jargon (e.g., code), and robust error handling across multiple platforms (Mac, iOS, browser).

This tool allows users to execute complex, multi-agent workflows defined in YAML format directly within the AI environment. It functions as an orchestration engine, sequentially invoking various specialized roles (agents) without requiring manual API key configuration. Ideal for structured tasks requiring collaboration between multiple personas.

XcodeBuildMCP is a unified skill set designed to streamline the entire mobile and desktop development lifecycle. It replaces raw command-line tools like xcodebuild, xcrun, and simctl, providing structured workflows for iOS, macOS, watchOS, tvOS, and visionOS. Capabilities include project discovery, managing simulator and physical device workflows, advanced UI automation (gestures, view inspection), robust logging, and deep debugging using LLDB. It simplifies complex build, test, and run operations across multiple platforms.

This skill guides users on creating, editing, and validating AI agent skills using Test-Driven Development (TDD) principles. It covers skill types, directory structure, SKILL.md formatting, and optimization strategies for discovery.

This tool analyzes and refactors code to detect and correct anemic domain models. It enforces rich domain modeling patterns (Entities, Value Objects, Aggregates, Domain Events), improving encapsulation and business logic ownership. Use it when validating, reviewing, or refactoring core domain logic to ensure adherence to Domain-Driven Design (DDD) principles.

This guide details the usage of go.uber.org/dig, a powerful reflection-based container for Dependency Injection in Golang. It covers advanced patterns like using `Provide`/`Invoke` for service registration, grouping parameters with `dig.In`, managing multiple outputs with `dig.Out`, and handling named/grouped dependencies. This is essential for reliably wiring complex application graphs at startup.