Design e Frontend

Esta skill aplica estilos de design ou estéticas nomeadas a interfaces frontend. Ela é acionada quando o usuário especifica um estilo, pergunta quais estilos são suportados ou solicita uma aparência específica.

Generate personalized music playlists by analyzing the user's music taste and generation feedback history. Triggers on any request involving playlist generation, music taste profiling, or personalized music recommendations. Supports multilingual triggers — match equivalent phrases in any language.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate exte...

OKX-aggregated DeFi product discovery and execution — for users who want OKX to find and route to the best protocol, WITHOUT naming a specific DApp. **If the user names ANY third-party protocol/DApp as the destination (Polymarket, Aave, Hyperliquid, PancakeSwap, Morpho, Raydium, Curve, Compound, Pendle, Clanker, pump.fun, Lido, GMX, ether.fi, Kamino, Orca, Meteora, Uniswap, Spark, dYdX, Yearn, etc

Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.

Create Zustand stores with TypeScript, subscribeWithSelector middleware, and proper state/action separation. Use when building React state management, creating global stores, or implementing reactive state patterns with Zustand.

오답노트 + 성공 패턴 자동 관리. CLI(Claude/Codex/Gemini)의 실패 패턴(gotchas)과 성공 패턴(learned)을 2계층(글로벌 + 프로젝트별)으로 기록하고 참조. 므네모(mnemo)가 생성하는 memory/ 폴더 안에서 크로스 CLI 참조 가능. 트리거 1 (참조): 작업 시작 시 gotchas + learned를 확인. 트리거 2 (기록): "실수였어", "이거 기록해", "gotcha 추가", "함정이었네", "오답노트", "이것도 주의사항", "이 패턴 좋다", "이거 기억해" 같은 표현 시. 트리거 3 (자발적 제안): CLI가 실수를 수정당하거나 성공 패턴이 반복될 때 기록을 제안.

World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implement

Build enhancer-driven gene regulatory networks (eGRNs) by integrating single-cell RNA-seq and ATAC-seq using SCENIC+, CellOracle base GRNs, Pando, FigR, DIRECT-NET, TRIPOD, and scMEGA. Covers the accessibility-defines-enhancers principle, peak-to-gene linking and its cell-composition confound, the paired-vs-unpaired decision, and TF-region-gene eRegulon triplets. Use when analyzing 10x multiome or

Guide for creating new Claude skills. Use this when creating a new skill, updating existing skills, or learning best practices for skill development.