Skill UI

An advanced debugging skill designed for AI agents. It utilizes gdb-cli to provide intelligent assistance for C/C++ programs, enabling the analysis of core dumps, debugging live processes, and investigating complex issues like crashes, deadlocks, and memory corruption. It correlates runtime state inspection with source code context for deeper insights.

A systematic protocol for repairing entire broken features or modules. It requires mapping all dependencies, tracing connections, and diagnosing issues before applying fixes. Unlike quick bug fixes, this method ensures comprehensive understanding of the feature scope, inbound/outbound dependencies, and root causes through five strict phases: Scope, Trace, Diagnose, Fix, and Verify.

Master the use of the `gh` CLI to interact with core GitHub features. This guide covers managing issues, checking Pull Request statuses, listing and debugging CI workflow runs, and executing advanced data queries via the GitHub API. Essential for automating DevOps workflows and debugging CI/CD pipelines directly from the terminal.

This agent facilitates comprehensive debugging and testing of iOS applications running on a simulated environment. It leverages XcodeBuildMCP to manage the entire lifecycle, including building, running, interacting with the UI (tap, type, gesture), taking screenshots, and capturing detailed runtime logs. Use it whenever you need to simulate real-world app testing or diagnose issues on a booted simulator.

This expert reviews and rectifies complex Swift Concurrency issues, such as actor isolation violations, Sendable safety breaches, and data races. It applies modern patterns (like `@MainActor` and `actor` usage) to ensure code adheres to Swift 6.2+ standards while minimizing behavior changes. Use it when debugging concurrency warnings or migrating legacy codebases.

This skill provides a comprehensive, structured workflow for diagnosing performance bottlenecks in SwiftUI applications. It guides users through a code-first review to detect common issues like invalidation storms, layout thrash, or heavy main-thread work. When code review is insufficient, it provides detailed guidance on collecting runtime evidence using Instruments, enabling precise root cause analysis and targeted remediation strategies.

Trackio is an essential library for logging, visualizing, and analyzing machine learning training experiments. It provides multi-interface support: a Python API for real-time metric logging and alert firing during training; a Command Line Interface (CLI) for retrieving historical metrics and alerts; and synchronization capabilities to Hugging Face Spaces for persistent dashboards. This tool is crucial for debugging, diagnosing training issues (like loss spikes), and automating ML workflow iteration.

A comprehensive operational guide for support teams to manage complex customer billing workflows. It assists operators in diagnosing billing anomalies, processing refunds, triaging charges, and recovering customer portals. Use this when investigating billing discrepancies, assessing churn risk, or ensuring accurate subscription state and revenue management.

A comprehensive skill for integrating development workflows directly with Jira. Users can retrieve, analyze, and update Jira tickets, including extracting testable acceptance criteria, transitioning status, adding comments, and searching issues using JQL. Supports both MCP-based and direct REST API interactions.

This skill acts as an expert data quality engineer to systematically assess dataset health before analysis or model training. It profiles data using specialized scripts to detect missing values, outliers, duplicates, and distribution shifts. The tool generates a Data Quality Score (DQS) and provides prioritized remediation plans to prevent data issues from corrupting downstream models or dashboards.

This tool runs comprehensive diagnostics on the current context mode environment. It checks the status of critical components, including runtimes, hooks, FTS5, plugin registrations, and versions for npm and the marketplace. Use this skill to quickly identify potential technical issues or configuration inconsistencies, ensuring smooth system operation.

This skill provides a comprehensive, dual-engine audit for content, covering both Search Engine Optimization (SEO) and Answer Engine Optimization (AEO), along with readability metrics. It generates detailed scores (out of 100) and provides a severity-ranked list of issues (Critical, Important, Polish) with specific, actionable fix instructions. Use it before publishing to ensure content achieves optimal search performance and high engagement.