Skill UI

This guide outlines critical reliability patterns for integrating advanced AI coding assistants into professional development workflows. It emphasizes best practices such as mandatory Git checkpointing, utilizing dedicated feature branches, breaking large tasks into incremental steps, and implementing comprehensive validation gates (linting, testing). Use this when developing fault-tolerant, AI-assisted applications to prevent accidental code breaks and maintain project stability.

A comprehensive guide to securing development workspaces using Windsurf. This skill teaches how to apply best practices for workspace isolation, prevent sensitive data (secrets, PII) from leaking into AI indexes, manage telemetry, and ensure compliance by configuring exclusion files and security rules.

Expert resource for designing, deploying, and optimizing serverless applications on the Cloudflare Edge Network. Covers advanced topics including Workers, KV, D1, Durable Objects, and R2 storage. Ideal for building high-performance, low-latency full-stack applications and implementing edge security features.

This guide provides a comprehensive walkthrough for developing and deploying Apify Actors. Actors are serverless, containerized applications designed for powerful tasks like web scraping, data processing, and complex automation. Learn the mandatory setup, template selection (Python, JS, TS), step-by-step development workflow, and crucial security best practices for building robust, production-ready data pipelines.

Guides branch completion by verifying tests, identifying the base branch, presenting merge/PR/keep/discard options, and cleaning up worktrees when appropriate.

An expert assistant for the Makepad UI framework in Rust. This skill helps users generate correct, boilerplate-free Rust code, understand basic app structure, manage event handling, and troubleshoot issues related to cross-platform GUI development. Use it when you are starting a new Makepad project or need foundational guidance on widget implementation and application lifecycle.

This skill generates a complete, opinionated, modern full-stack Rails application boilerplate. It sets up a robust tech stack including Rails 8, PostgreSQL, React, Inertia.js, Vite, Tailwind CSS, Sidekiq, and Redis. Designed for developers who need a starting point that adheres to best practices for database structure (UUIDs, JSONB), background job processing, comprehensive testing, and modern frontend development (TSX). Ideal for bootstrapping complex, production-grade web services.

This skill outlines a comprehensive methodology for designing, building, and deploying robust LLM-powered applications. It covers assessing task-model fit, designing modular pipelines (acquire -> prepare -> process -> parse -> render), and managing state using file systems to ensure scalability and reliability in AI systems.

This skill guides the development of EarLLM One, a complex Android application. The app captures real-time audio from Bluetooth earbuds, transcribes the voice using STT, sends the text input to a Large Language Model (LLM) via a robust pipeline, and plays the response back using TTS. It requires deep knowledge of Kotlin, Android development, Bluetooth profiles (A2DP/HFP), and advanced audio routing.

This agent simulates the profound cognitive structure, aesthetic intuition, and strategic mindset of Steve Jobs. It is designed for users who need to approach product development, design, or business strategy with a visionary, minimalist, and highly curated perspective. Use it to strip away complexity, define core user experiences, and articulate powerful, simple narratives.

An expert guide for developing production-grade AI applications, chatbots, and generative UIs using the Vercel AI SDK, Next.js, and React. Covers core concepts including streaming text (`streamText`), managing chat state (`useChat`), implementing complex tool/function calling, and ensuring robust structured data generation (JSON schemas) across multiple LLM providers.

This utility converts a single, high-level objective into a comprehensive, step-by-step build plan suitable for complex, multi-agent, or multi-session engineering projects. It automatically handles dependency mapping, detects parallel steps, and structures each step with self-contained context briefs, ensuring any new agent can execute it without prior knowledge. Ideal for large-scale refactoring or feature development spanning multiple PRs.