Skill UI

A skill for designing evidence and validation strategies for academic manuscripts submitted to the Journal of Systems Engineering. It covers standards for numerical experiments, simulations, real data, case studies, and empirical research, ensuring claims are supported by appropriate evidence rather than generic robustness checks.

This expert skill performs non-intrusive static analysis to thoroughly audit AI skills and bundles. It identifies malicious patterns, data leaks, system stability risks, and obfuscated payloads across major operating systems (Windows, macOS, Linux/Unix) and mobile platforms (Android/iOS). Use it when verifying skill legitimacy or performing deep cross-platform security reviews.

Automate the rotation of sensitive credentials, including RDS database passwords, API keys, and OAuth tokens, using AWS Secrets Manager and Lambda. This skill ensures secure credential lifecycle management, helping maintain system security and compliance by automatically updating credentials for various AWS and third-party services.

This comprehensive skill provides a security posture assessment for AWS environments. It uses AWS CLI commands to audit critical security areas, including IAM policy review, network security groups, data encryption status (EBS, S3, RDS), and logging mechanisms (CloudTrail, VPC Flow Logs). Use this to proactively identify misconfigurations and ensure adherence to security best practices and compliance standards.

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

Run comprehensive, read-only exposure checks against your local machine or project directories in response to security advisories and CVEs. This tool systematically checks various ecosystems (Node.js, Python, Homebrew, etc.) to generate a structured, non-invasive audit report, helping users understand their actual risk exposure without making any system changes.

A comprehensive guide featuring best practices and patterns for building robust GitLab CI/CD pipelines. Covers multi-stage deployments, containerization (Docker), infrastructure as code (Terraform), security scanning, caching strategies, and advanced GitOps workflows for automated testing and deployment to Kubernetes.

A comprehensive guide detailing how to implement declarative, Git-based continuous delivery for Kubernetes. It covers setup using industry-leading tools like ArgoCD and Flux CD, adhering to OpenGitOps principles for automated, reliable, and traceable application deployments and infrastructure management.

Provision, configure, and monitor NVIDIA GPU servers for AI inference and training workloads, including driver/CUDA installation, Docker GPU support, MIG partitioning, and health monitoring.

This skill provides comprehensive guidance on establishing secure, high-performance connectivity between on-premises data centers and major public cloud providers (AWS, Azure, GCP). It covers various connection options, including Site-to-Site VPN, AWS Direct Connect, Azure ExpressRoute, and GCP Cloud Interconnect. Use this skill to design and implement complex hybrid network patterns (e.g., Hub-and-Spoke, Multi-Cloud), ensuring high availability, proper routing (BGP), and adherence to security best practices.

KubeStellar Console is an open-source, multi-cluster Kubernetes dashboard (CNCF project) that provides advanced operational capabilities powered by an MCP server and built-in AI agent skills. It helps manage complex deployments across edge and cloud environments, offering AI-assisted troubleshooting, performance testing, and deep integration with major CNCF projects like Argo and Istio.

This skill generates standardized, production-ready `mise.toml` configurations. It helps developers standardize runtime versions across mixed-language projects (e.g., Node.js, Python, Go, etc.) and CI/CD pipelines, eliminating the need for multiple legacy version managers like asdf or nvm. Ideal for ensuring reproducible, consistent development environments.