Skill UI

An interactive tool designed to discover, select, and assemble specialized teams of AI agents. It supports structured agent collections across different domains (e.g., Engineering, Marketing). Users select multiple roles for a specific task, and the skill launches them in parallel, synthesizing their independent findings into a unified report, including consensus and conflict analysis.

Soft Predict Future is a structured foresight engine that triggers whenever the user asks about future outcomes or scenarios. It enforces a nine-step analytical pipeline (validation, signal collection, scoring, driver extraction, etc.), highlights required searches and inputs, and directs the user to web-enabled reasoning for predictive analysis.

Guides teams through classifying and triaging declared security incidents, scoring severity, filtering false positives, routing escalations, and starting forensic collection consistent with NIST SP 800-61.

Collection of battle-tested PyTorch training recipes covering architecture selection, optimizers, LR scheduling, precision tips, and debugging to train or fine-tune LLMs, vision, diffusion, and biomedical models with high GPU throughput.

A comprehensive collection of agent skills for rigorously auditing digital interfaces and user flows. It evaluates designs against 168 research-backed UX/UI principles, detects common design antipatterns, and provides specialized review for AI-powered interfaces, ensuring adherence to modern best practices.

Skill for implementing Firebase Crashlytics in Flutter apps. Covers fatal/non-fatal error capture, async and isolate exceptions, crash customization with keys/logs/user IDs, symbol upload, opt-in data collection, and debug build disables.

This skill explains how to implement Firebase In-App Messaging in Flutter apps: setting up the SDK, triggering or suppressing messages programmatically, managing opt-in data collection for privacy compliance, testing on specific devices, and creating targeted campaigns.

A comprehensive, generics-first utility library designed for Go developers who prefer declarative, functional programming patterns over manual loops. It provides 500+ type-safe functions for common data transformations (Map, Filter, Reduce, GroupBy, etc.) on slices, maps, and strings. By defaulting to immutable operations, it ensures thread safety and predictable state changes. The library also offers specialized packages (lop, lom, loi) to address performance bottlenecks, such as CPU-bound parallel processing or lazy evaluation, allowing engineers to choose the optimal approach for their c...

A comprehensive toolkit designed to automate core Shopify operations via Rube MCP. It provides structured workflows for managing all key aspects of an e-commerce store, including products (listing, creation), orders (tracking, retrieval), customers, collections, and inventory levels. Utilizes direct tool calls for listing, searching, and bulk operations, making it ideal for integrating complex business logic into automated systems.

This comprehensive toolkit automates critical Webflow operations, including managing CMS collections (create, update, delete), site publishing, page inspection, and asset uploads. By connecting via Rube MCP, it allows developers to programmatically interact with Webflow's backend, making it ideal for implementing automated content workflows, CI/CD pipelines, and large-scale content management systems.

WizTelemetry Logging is a core extension component within the KubeSphere Observability Platform, designed for comprehensive log collection, processing, and storage. It supports advanced log collection architectures, including collecting container stdout/stderr logs (via vector-logging) and collecting logs directly from the container filesystem (via logsidecar-injector). Use this guide to understand its configuration, dependencies, and how to query logs using the dedicated API.

This skill provides programmatic access to the CZ CELLxGENE Census, a comprehensive collection of versioned public single-cell and spatial transcriptomics data. It enables efficient querying of population-scale cell metadata, gene expression slices, and embeddings without downloading entire datasets. Suitable for analyzing human, mouse, and other organism data across tissues and diseases. Integrates with Scanpy, AnnData, and TileDB-SOMA for large-scale analysis and machine learning workflows.