Skill UI

A comprehensive guide to building robust, production-ready GraphQL APIs. This skill covers schema design (SDL/code-first), implementing efficient resolvers with DataLoader for batching, handling real-time subscriptions via WebSockets, and integrating field-level authorization and complexity limiting. Supports major runtimes like Node.js and Python.

An expert guide to designing secure, performant GraphQL APIs covering schema design, resolvers, federation, DataLoader batching, subscriptions, and client integration with Apollo/urql, including advice on when REST may be preferable.

This skill guides the design and implementation of complex GraphQL APIs. It specializes in schema design, utilizing Apollo Federation for distributed microservices, optimizing resolvers with DataLoader for N+1 prevention, and implementing real-time subscriptions. It covers security, complexity analysis, and adherence to best practices for building scalable, high-performance graph architectures.

Guidance for building robust GraphQL services: schema design with Relay-style pagination, resolver patterns that leverage per-request DataLoader for N+1 prevention, subscription handling, and structured error payloads to simplify client integrations.

Automates GraphQL resolver creation for backend teams, giving step-by-step guidance, industry best practices, and production-ready code/configs to validate resolvers across Node.js, Python, Go, database design, caching, messaging, and microservices.

uv is an extremely fast Python package installer and resolver written in Rust. This guide provides a comprehensive workflow for modern Python project management and dependency handling. Use this skill to set up new projects quickly, manage dependencies much faster than traditional tools like pip, resolve complex conflicts, and optimize CI/CD pipelines, especially when dealing with monorepos or needing reproducible builds.

Configure NextDNS as an encrypted DNS resolver (DoH/DoT) to enforce zero trust principles at the network layer. This skill guides users on deploying real-time threat intelligence filtering, blocking malicious domains, preventing cryptojacking, detecting DNS rebinding, and enforcing strict organizational DNS policies across endpoints, aligning with modern cybersecurity standards.

A comprehensive guide on extending and customizing GraphQL APIs using the GraphQLSchemaFactory pattern. Learn how to add custom queries and mutations, define type definitions, and implement complex resolvers with per-request dependency injection (DI). Ideal for developers needing to inject backend services, use cases, and sophisticated business logic into their existing GraphQL schema.

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

A comprehensive guide for building scalable and performant GraphQL APIs using Golang. Covers best practices including defining schema (SDL), implementing robust resolver patterns, handling pagination with Relay cursors, and critically, utilizing DataLoaders to prevent N+1 database query issues. Essential for backend engineers designing high-quality services.

This skill guides the planning and review process for complex home or small-lab network changes. It covers creating staged migration plans for VLAN segmentation, implementing local DNS resolvers (like Pi-hole), setting up secure VPN access, and ensuring network safety through detailed inventory checks and rollback procedures. It emphasizes security best practices and trust zoning.

This skill transforms vague, unclear, or half-formed business opportunities and brief descriptions into highly structured, actionable problem statements. It guides the user through a three-stage process: reframing the core questions, rigorously defining in-scope and out-of-scope boundaries, and designing a minimum viable research plan. It ensures that ambiguous inputs are converted into clear, executable steps, allowing the user to respond with confidence rather than asking for more clarification meetings.