Skill UI

This specialized guide is essential for developers migrating projects from Godot 3.x to Godot 4. It systematically covers major technical updates, including GDScript 2.0 syntax changes, mandatory `@export` annotations, adopting the modern `create_tween()` system, and updating signal connections and coroutine handling from `yield` to `await`. Use this resource to ensure a smooth and efficient engine upgrade.

Set up comprehensive CI/CD pipelines for PostHog integrations using GitHub Actions. This guide covers mocked unit tests (no API key needed), robust integration tests against a development PostHog project, and automated deployment annotations to mark releases in your PostHog timeline. Ideal for developers ensuring data quality and traceability across all environments.

A specialized skill for building modern Vue 3 applications using pure JavaScript, completely avoiding TypeScript. It implements the Composition API, configures modern build tools like Vite, and ensures robust type safety by utilizing JSDoc annotations (@param, @returns, @typedef) instead of a compiler. Ideal for teams preferring vanilla JavaScript, migrating from Vue 2, or needing quick prototypes without a TS setup.

Manage microscopy data with the OMERO Python API: access projects/datasets/images, retrieve and analyze pixel data, handle ROIs and annotations, store results in tables, and automate batch workflows for high-content screening.

This skill helps developers write idiomatic, high-quality Dart and Flutter code. It covers naming conventions, type annotations, code style, import structure, and documentation standards. Use it for code reviews, refactoring, and enforcing best practices in Dart projects.

This skill generates deep, clickable URLs to various resources within the Arize monitoring UI. It supports linking to specific traces, spans, sessions, datasets, evaluators, and annotation configurations. It is essential for sharing specific debugging artifacts or navigating directly to key data points within the MLOps platform by requiring precise resource IDs and time ranges.

Provides an expert Spring Boot 4 testing guide that explains the test pyramid, slice annotations, AssertJ-centric assertions, MockMvcTester, RestTestClient, Testcontainers, and practical coverage goals.

This skill guides the setup and configuration of the CAST AI Workload Autoscaler, enabling dynamic right-sizing of pod resource requests (CPU and Memory). It automatically adjusts resources based on actual usage, significantly reducing cloud over-provisioning costs. Use this guide to implement workload scaling policies, configure resource limits via Kubernetes annotations, and monitor scaling events in Kubernetes environments.

This guide provides advanced patterns for composing robust, multi-step Large Language Model (LLM) workflows using LangChain 1.0 core runnables. Learn to implement parallel retrievals (RunnableParallel), conditional routing (RunnableBranch), and state management. It also addresses common pitfalls like silent KeyErrors due to mismatched dictionary shapes, providing solutions using debug probes and type annotations for reliable RAG, classification, and extraction pipelines.

This workflow automates the creation of step-by-step documentation guides using the TechSmith Snagit COM API and PowerShell. It first captures a series of sequential screenshots for a guide, and then uses a batch process to open and annotate these images within the Snagit Editor, ensuring consistency and efficiency in creating professional tutorials.

This guide details the architectural and implementation patterns for building modular applications or microservices using the tinystruct Java framework. It covers core concepts like using the @Action annotation for dual routing (CLI/HTTP), managing request state with Context, and using native Builder for JSON serialization, ensuring a lightweight and structured development environment.

A powerful Python skill for adding professional callouts, arrows, and labels to various images, including screenshots, diagrams, and architecture documents. It allows users to visually highlight specific areas or changes. The advanced `annotate.py` module provides algorithmic label placement, optimizing for readability and preventing overlaps. Ideal for creating clear PR descriptions, documenting changes, or building annotated demo assets.