Skill UI

A framework-agnostic, builder-based SEO system designed for React and React Native-for-web applications. It centralizes site identity (title, description, OG tags) in a single source of truth, ensuring all metadata, canonical URLs, and structured data (JSON-LD, sitemap, robots.txt, RSS) are consistent, machine-readable, and automatically generated for every route.

This skill provides comprehensive access to the Hugging Face Hub ecosystem via MCP server tools. Users can search for state-of-the-art models, datasets, and research papers, retrieve detailed repository information, fetch documentation, run compute jobs on GPU/CPU, and interact with Gradio Spaces as fully functional AI tools. Ideal for ML development, research, and application prototyping.

The `hf-mem` skill estimates the necessary VRAM or system memory required to load Safetensors or GGUF model weights for inference directly from the Hugging Face Hub. It uses efficient HTTP Range requests, avoiding local downloads. Users can determine if a model fits on their GPU or instance, including optional estimations for the KV cache and setting limits like maximum sequence length.

This skill provides an autonomous, repository-wide pipeline for auditing and fixing complex logical inconsistencies. It systematically executes stages including health checks, deep review, locating divergences, generating fixes, and performing diff-verification until the codebase is deemed clean. Ideal for maintaining high code quality and resolving deep, systemic bugs across entire projects.

This sophisticated skill is designed to locate the root cause of a confirmed software failure. It performs a systematic, semi-formal tracing process: first tracing backward from the observed failure point (using provided stack traces, assertions, or error messages) to identify the original premise, and then tracing forward to confirm the symptom. It outputs a highly structured report detailing the divergence, premises, and remedy.

This skill is designed to identify subtle and complex logic bugs within a single code file or function. It employs a semi-formal execution tracing methodology, systematically breaking down the suspected bug into five stages: Premises (expected state), Trace (execution path), Divergence (actual deviation), Trigger (reproduction case), and Remedy (fix). It is ideal for scenarios where users suspect code is wrong but cannot specify a concrete failure point.

This skill guides the entire lifecycle of repeatable AI agent loops. Use it to discover recurring work patterns within codebases, find established solutions in a library, or interview users to craft bounded, effective loops. It supports auditing, repairing, running, and preparing AI workflows for publication, treating the loop as a robust feedback system.

A systematic skill designed to investigate data incidents, including freshness delays, volume anomalies, schema changes, and ETL failures. It guides the agent through a comprehensive process using Monte Carlo's observability metadata and optional direct data querying to pinpoint the root cause.

Provides championship-grade repository hygiene and health checks. It systematically audits critical areas, including dependency health, CI/CD pipeline alignment, documentation synchronization, and detecting stray artifacts. The tool generates a prioritized, actionable cleanup plan and offers auto-fix capabilities to keep codebases pristine and production-ready.

A fast, grep-based linter that checks for common design system violations in CSS and component code, such as hardcoded colors, raw pixel values, and deprecated syntax. It provides immediate automated feedback to ensure code adheres to established design tokens and best practices.

This skill systematically scans Apple's comprehensive developer documentation, specifically targeting SwiftUI. It identifies deprecated APIs, finds their modern replacements, and updates the expert skill's reference guide. Use this when required to refresh deprecated features, check for new API deprecations after an iOS/Xcode update, or maintain the most current best practices for SwiftUI development.

Design and schedule recurring, self-running marketing workflows with defined triggers, cadences, guardrails, and stop conditions. Orchestrate SEO, ads, content, outbound, and retention loops as always-on systems.