Skill UI

This skill assembles scored competitor profiles and market findings into a comprehensive, decision-grade report. It guides the user to answer critical client questions: who to compete with, how to differentiate, and where the defensible white-space is. Ideal for board presentations, strategic planning, and creating highly defensible client deliverables.

This tool scans project dependencies to detect known Common Vulnerabilities and Exposures (CVEs) and outdated packages. It is essential for security auditing of third-party packages, mandatory before major releases, or immediately after dependency updates. It helps teams assess risk levels (critical, high, moderate) and can even attempt automatic fixes via the CLI.

This skill provides comprehensive automation for managing GitHub workflows across the entire development lifecycle. It covers detailed issue triage, PR review status checks, CI/CD failure debugging, official release management, and security monitoring using the GitHub CLI. Ideal for maintaining open-source project health and streamlining team development processes.

A powerful tool designed to scaffold sophisticated, custom AI agent harnesses using the metaharness CLI. It supports various templates (e.g., coding, devops, marketing) and AI hosts (e.g., Claude, Codex). Crucially, it operates with maximum safety, defaulting to a dry-run mode and refusing to write to the calling repository root, ensuring controlled and predictable development workflows.

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.

A comprehensive guide to building HIPAA, GDPR, and other global compliance systems for healthcare applications. This pattern outlines best practices for protecting Protected Health Information (PHI) and Personally Identifiable Information (PII) by implementing robust access controls, Row-Level Security (RLS), and mandatory audit trails. Essential for any feature handling patient or clinical data.

This tool registers a Cognitum Seed IoT device by specifying its endpoint. It establishes a SeedClient connection, fetches the device's identity, and assigns an initial trust level. It supports optional pairing token usage for advanced setup and provides device status checks.

A comprehensive guide covering best practices for building and debugging Nuxt 4 applications. It details patterns for ensuring hydration safety, optimizing data fetching with `useFetch` and `useAsyncData`, managing complex routing rules, and implementing lazy loading for superior performance across SSR and client-side environments.

This advanced pipeline orchestrates complex feature development based on Request for Comments (RFCs). It breaks down monolithic changes into small, independently verifiable work units, managing dependencies through a Directed Acyclic Graph (DAG). It includes multiple quality gates, dedicated unit testing, and a safe merge queue to ensure robust integration and controlled deployment.

A comprehensive guide detailing idiomatic React 18/19 patterns. Covers core principles like component purity, side effect management, hooks discipline, state location decision trees, and advanced topics such as Server/Client Component boundaries (RSC), Suspense, error handling, and using React 19 form actions for building robust, performant, and accessible UIs.