Skill UI

Guides Claude Code plugin authors through creating event-driven hooks that validate tool usage, react to outcomes, and gate completion with prompt-based or command hooks, covering PreToolUse, PostToolUse, Stop, Session events, and session context loading.

A comprehensive guide covering Internationalization (i18n) and Localization (L10n) best practices. It details how to build applications that can support multiple languages, regions, and text directions (RTL). Covers implementation patterns for React, Next.js, and Python, along with essential guidelines for handling date/number formats and managing translation keys.

This skill leverages Google Gemini's advanced image generation model to create high-quality, context-specific visuals. It is essential for developers needing placeholder images for UIs, generating detailed diagrams for technical documentation, or visualizing abstract concepts, logos, and assets across cross-platform projects (Windows, macOS, Linux).

Guides multi-agent workflows through an iterative context retrieval loop—dispatching broad queries, evaluating relevance, refining criteria, and looping up to three times so sub-agents gather exactly the files they need without overwhelming limits.

This skill provides step-by-step guidance for creating production-ready Kubernetes manifests. It covers essential resources including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims. Use this skill when defining complete, robust containerized application architectures, managing network connectivity, stateful workloads, and ensuring adherence to Kubernetes best practices like resource limits and security contexts.

This tool provides comprehensive Python solutions for processing batches of text-to-video requests using the Kling AI API. It handles controlled parallelism, rate-limiting, and detailed status tracking. Use this when building robust content pipelines that require generating multiple videos efficiently from a list of prompts, supporting synchronous, asynchronous, and webhook callback methods.

A comprehensive guide for developers on utilizing the Kling AI Text-to-Video REST API. This skill provides minimal working examples in Python and Node.js, demonstrating the complete workflow: submitting a text prompt, polling the task status, and retrieving the final generated video URL. Ideal for integrating advanced AI video generation capabilities into development projects.

Master the art of building robust, production-grade LLM chains using LangChain Expression Language (LCEL). This guide covers advanced composition patterns, including sequential, parallel, and conditional branching chains. It also details prompt templating, structured output parsing (JSON/Zod), and context injection, enabling the creation of complex, multi-step AI pipelines.

This bundle collects comprehensive diagnostic evidence for Langfuse support tickets and troubleshooting. It gathers system environment details (Node.js, Python, OS), installed SDK versions, API connectivity status, and redacted application logs. Use this when encountering persistent or complex Langfuse issues to provide full context to support teams.

This guide provides production-grade architecture patterns for implementing robust LLM observability using Langfuse. It covers singleton SDK setup, context propagation across asynchronous boundaries, Express middleware for automatic tracing, and cross-service trace correlation using OpenTelemetry. Ideal for designing enterprise-level, scalable tracing infrastructure for LLM applications.

Provides a senior migration architect workflow that researches legacy codebases, maps bounded contexts, and writes Strangler Fig-based modernization roadmaps so other teams can incrementally reshape systems.

This guide details the process of building Model Context Protocol (MCP) servers. These servers are crucial for enabling Large Language Models (LLMs) to interact with external APIs and services, facilitating complex, real-world task completion. It provides comprehensive coverage on architectural planning, choosing appropriate languages (Python, TypeScript, C#), and selecting transport mechanisms (HTTP, stdio) for robust integration within enterprise ecosystems like Azure and Foundry.