Skill UI

This skill provides a comprehensive, structured audit of any design system. It assesses component coverage gaps against production UI, monitors design token consistency (color, spacing, typography), evaluates documentation quality, and checks for accessibility compliance. The output includes an overall health score and a prioritized remediation roadmap, making it essential for design leadership and engineering teams maintaining shared component libraries.

This skill performs a comprehensive audit of Figma component libraries. It checks for naming inconsistencies, component coverage gaps, variant completeness, and overall design system health. The output provides a structured report with prioritized issues, actionable naming conventions, and a step-by-step fix plan, ensuring design consistency across products.

This guide helps define a complete observability stack for any service. It systematically covers the Four Golden Signals (latency, traffic, errors, saturation), guiding users to define core metrics, set Service Level Objectives (SLOs), configure actionable alerting rules, and structure comprehensive monitoring dashboards. Essential for establishing robust SRE practices and documenting system health standards.

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.

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.

KubeEye is a comprehensive cluster inspection tool designed for Kubernetes environments, particularly within KubeSphere. It systematically detects issues across workloads, nodes, and configurations by integrating multiple policy engines, including OPA/Rego, PromQL, file integrity checks, kernel parameter validation, and systemd health checks. Users can define custom inspection rules (InspectRule), schedule checks (InspectPlan), and retrieve detailed reports (InspectResult) to ensure cluster compliance and stability.

A comprehensive tool for querying, storing, and managing complex knowledge across multiple agent sessions. AgentDB utilizes advanced techniques including semantic routing, hierarchical recall, causal graph construction, and context synthesis. Use this skill when your application requires robust, multi-faceted knowledge retrieval and reasoning based on structured and unstructured data. It provides a structured workflow for checking system health, starting sessions, storing knowledge in tiers (working, episodic, semantic), and searching learned patterns.

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

This tool provides a comprehensive overview of the federation's operational status. It allows users to check overall health, list connected peers along with their trust levels and scores, and summarize crucial metrics like active sessions, message exchanges, PII redactions, and detected threats. Use it to inspect cross-installation agent connectivity and ensure the stability of the federated system.

This library provides comprehensive patterns for building robust Clinical Decision Support Systems (CDSS) integrated into Electronic Medical Records (EMR). It ensures patient safety by implementing critical checks such as drug interaction screening, weight/age/renal-adjusted dose validation, and standardized clinical scoring (e.g., NEWS2). The engine uses pure functions, guaranteeing high testability and reliability for critical medical insights.

A comprehensive guide detailing architectural patterns for developing robust Electronic Medical Record (EMR) and Electronic Health Record (EHR) systems. Covers critical areas like patient safety protocols, structured clinical workflows, drug interaction checking, audit trail implementation, and WCAG accessibility standards. Essential for building highly reliable and compliant healthcare IT solutions.

An automated verification system designed for critical healthcare application deployments (EMR/EHR). This harness enforces stringent patient safety standards by running multiple mandatory test gates, including Clinical Decision Support System (CDSS) accuracy, Protected Health Information (PHI) leakage prevention, and data integrity checks. A single failure in critical gates automatically blocks deployment, ensuring regulatory compliance and optimal patient safety in the CI/CD pipeline.