Skill UI

Guides authors through adapting test-driven development to agent skills documentation, covering when to create skills, required background, directory structure, and how to run pressure scenarios to ensure compliance before publishing.

This skill provides comprehensive operational controls for long-lived, cloud-hosted agent workloads. It manages the entire lifecycle—from deployment and scaling to observability and security. Features include detailed monitoring (logs, metrics, traces), safety controls (kill switches, least privilege), and robust change management processes (rollout, rollback, auditing). Ideal for mission-critical microservices and background agents.

This infrastructure provides a robust solution for running powerful AI agents in remote, sandboxed environments. It overcomes the limitations of local execution by ensuring unlimited concurrency, consistent environments, and collaborative features. Use this to build complex background coding agents, multi-client interfaces (e.g., Slack, Web), or scale agent workloads far beyond local machine constraints.

This assistant specializes in the Makepad shader system. It helps users write, debug, and understand complex shader code using SDF2d and GLSL principles. Use it when developing custom widget backgrounds, advanced graphics, gradients, or visual effects that require low-level GPU rendering control within the Makepad framework.

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 provides best practices for structuring complex, production-ready applications built with Makepad. It details robust asynchronous communication patterns, showing how to integrate the Tokio runtime, manage state synchronization, and handle data flow between the main UI thread and background worker tasks using MPSC channels and SignalToUI. Essential for developing advanced chat clients or data streaming services.

This intelligent studio acts as a visual creative director, automatically routing image requests to the optimal specialized AI model. It handles hyper-realistic portrait generation (for influencers/professional photos) and advanced artistic creation, illustration, and photo manipulation (upscale, inpainting, background removal). Use it for professional content creation requiring specialized visual expertise.

Creates photorealistic or stylized images via Stability AI (SD3.5/Ultra/Core) with text-to-image, img2img, inpainting, upscale, background removal, erase, and search-replace modes for artistic or production-ready output.

Tmux is a powerful terminal multiplexer that enables users to manage multiple sessions, windows, and panes within a single terminal connection. It is essential for maintaining persistent connections on remote servers (surviving SSH disconnects), running long-term background jobs, and automating complex, multi-pane workflows directly from shell scripts, significantly enhancing remote development efficiency.

This comprehensive guide provides an end-to-end solution for implementing Firebase Cloud Messaging (FCM) in Flutter applications. It covers platform-specific setup for iOS, Android, and Web, detailing how to handle messages in foreground, background, and terminated states. Key topics include managing notification permissions, handling token lifecycles, and implementing reliable cross-platform push notification logic.

Generates polished investor and sales pitch decks as a single .pptx with gradient backgrounds, charts, tables, stat callouts, and speaker notes on every content slide for fundraising, product launches, or enterprise proposals.

This skill enables the generation of high-quality, cinematic videos using a highly structured prompt format (JSON). Users define detailed cinematic elements—including background, characters, camera movements, dialogue, and audio—and can optionally provide a reference image to guide the visual style or content of the final output. It automates the complex AIGC video generation workflow.