Skill UI

A comprehensive guide for building production-quality, highly accessible, and responsive user interfaces. Covers advanced topics including component architecture (composition over configuration), robust state management patterns (Context, Redux, Server State), adherence to design systems, and meeting WCAG accessibility standards. Use this skill when developing or refining complex user-facing components that require professional polish and maintainability.

Guides multi-round investigation of any GitHub repository, combining API queries, discovery searches, and deep dives to produce structured markdown reports with summaries, timelines, metrics tables, and Mermaid diagrams for executive-ready briefs.

This comprehensive guide covers structured concurrency patterns in Go, focusing on goroutines, channels, mutexes, and various sync primitives. It provides principles for writing, reviewing, and auditing concurrent code to ensure leak-freedom, correct ownership management, and robust error handling, covering topics like context propagation and race condition avoidance.

A comprehensive guide for advanced Go developers, detailing the internals, optimal usage, and performance pitfalls of core data structures like slices, maps, and arrays. It covers capacity growth mechanics, preallocation strategies using `make` and `slices` package functions, and best practices for choosing between various standard library containers (e.g., `strings.Builder` vs `bytes.Buffer`). Essential for writing highly efficient, memory-safe Go code.

This skill provides comprehensive observability tooling for Go services, covering the five essential signals: structured logging (slog), Prometheus metrics, OpenTelemetry tracing, continuous profiling, and RUM. Use it for proactive production monitoring, correlating logs with traces, setting up SLOs, and ensuring all new features are fully instrumented for robust diagnosis.

Defensive Golang guidance for avoiding panics, nil traps, append aliasing, overflow, float comparison bugs, and resource leaks. Useful for writing safer code and reviewing runtime risks.

A comprehensive, type-safe in-memory caching library for Go, designed for advanced system architecture. It supports nine sophisticated eviction algorithms (like W-TinyLFU, LRU, LFU, ARC) to optimize cache hit rates based on specific access patterns. Key features include TTL management, loader chains for read-through caching (with singleflight deduplication), sharding, and Prometheus metrics. Ideal for high-frequency services needing to reduce database load and latency.

A comprehensive, generics-first utility library for Go, providing over 500 type-safe, functional helpers (like Map, Filter, Reduce, GroupBy) for slices, maps, and channels. Designed to replace manual, verbose loops with declarative code. It supports immutable operations by default and offers progressive complexity variants (lo, lop, lom, loi) to handle different performance needs, from standard transforms to CPU-bound parallelism and lazy iteration. Ideal for writing clean, maintainable, and performant Go code.

A type-safe, generics-first library for implementing ReactiveX streams in Golang. It provides declarative, composable pipelines for handling infinite, asynchronous data sources (like WebSockets or timers) with automatic backpressure, robust error propagation, and full Go context integration. Ideal for building real-time, event-driven architectures.

A comprehensive guide to safely deploying new features to production. This methodology emphasizes moving beyond simple deployment by incorporating a detailed pre-launch checklist (covering security, performance, and accessibility), utilizing feature flags, and executing staged rollouts (Canary releases). It details best practices for observability, monitoring key metrics, and planning effective rollbacks.

This skill generates highly structured DESIGN.md files, acting as a semantic design system for Google Stitch. It translates complex, anti-generic frontend principles—including typography, color calibration, component behavior, and motion physics—into actionable, natural-language rules. Use it as the single source of truth to guide AI in generating premium, non-clichéd, professional user interfaces.

This skill is designed to retrieve and display detailed usage metrics for GitHub Copilot within organizations and enterprises. Users can analyze adoption rates, total suggestions, acceptance rates, and chat interactions, broken down either by the entire organization/enterprise or on a per-user basis. It supports querying data for specific historical dates using GitHub CLI and REST API.