Skill UI

Set up comprehensive debugging environments, distributed tracing, and diagnostic tools for development and production. Configure tracing, logging standards, and troubleshooting workflows to diagnose multi-service issues efficiently.

Define and run multi-container Docker applications using declarative YAML configuration. Ideal for local development, setting up environments, managing service dependencies, and creating reproducible setups. Supports networking, volumes, and resource limits.

This skill enables autonomous multi-step research using Google's Gemini Deep Research Agent. Users can initiate queries, monitor progress, and collect cited reports for market analysis, literature reviews, or competitive scans. It requires a Gemini API key and Python environment. Ideal for tasks needing structured, source-grounded reports beyond simple web searches.

This skill provides comprehensive patterns for creating efficient GitLab CI/CD pipelines. It covers automated testing, building, deployment strategies, Docker integration, multi-environment configurations, Terraform workflows, security scanning, and caching optimization to streamline DevOps processes.

Comprehensive guidance for creating, organizing, and managing Helm charts to package and deploy Kubernetes applications. Covers chart creation, templating, multi-environment deployments, and repository setup.

Hono is a minimal and ultrafast web framework built entirely on Web Standards (Request/Response/fetch). It allows developers to build high-performance APIs and full-stack applications that run seamlessly across multiple environments, including Cloudflare Workers, Deno, Bun, and Node.js. It is ideal for edge deployment, Backend for Frontend (BFF) layers, and type-safe backend services.

Build background coding agents in remote sandboxed environments with image registries, warm pools, snapshots, and self-spawning sessions for scalable multiplayer execution.

Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims. Apply best practices, resource limits, health checks, and security contexts for multi-environment deployments.

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 automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

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.

Safely select and switch between multiple n8n MCP instances (production, staging, etc.) before performing operations. Prevents silent misrouting by verifying the target instance, especially for credential writes. Ensures correct environment targeting for workflow automation tasks.