Explorar skills

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 external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Guia para criar e configurar agentes AgenticX com papéis, objetivos, ferramentas, provedores de LLM e estratégias de execução. Use quando o usuário quiser criar agentes, atribuir ferramentas a agentes, configurar backends de LLM, configurar a execução de agentes ou construir sistemas multiagentes.

Master prompt engineering for AI models: LLMs, image generators, video models. Techniques: chain-of-thought, few-shot, system prompts, negative prompts. Models: Claude, GPT-4, Gemini, FLUX, Veo, Stable Diffusion prompting. Use for: better AI outputs, consistent results, complex tasks, optimization. Triggers: prompt engineering, how to prompt, better prompts, prompt tips, prompting guide, llm promp

Construa aplicações priorizando IA com pipelines RAG, embeddings, bancos de dados vetoriais, fluxos de trabalho agentivos e integração de LLMs. Domine engenharia de prompts, chamada de funções, respostas em streaming e otimização de custos para o desenvolvimento de IA pós-2025.

Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.

Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues. Use when asked to "review this PR", "code review", "pre-landing review", or "check my diff". Proactively suggest when the user is about to merge or land code changes. (gstack)

Use when rewriting, sharpening, or producing a prompt for Claude or another current frontier model. Sets standing rules for getting better LLM output through better prompts. Loaded by /kanso-task; not directly invoked by the user.

Integra aplicativos web React+Vite com o bodhi-js-sdk para integração local de LLM. Esta skill é usada para configurar, implantar ou solucionar problemas de conexão e autenticação do bodhi-js-sdk.

Cross-model benchmark for gstack skills. Runs the same prompt through Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens, cost, and optionally quality via LLM judge. Answers "which model is actually best for this skill?" with data instead of vibes. Separate from /benchmark, which measures web page performance. Use when: "benchmark models", "compare models", "which mode

World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

Estrutura de agente de IA biomédica autônoma para executar tarefas de pesquisa complexas em genômica, descoberta de medicamentos, biologia molecular e análise clínica. Use esta skill para pesquisa biomédica multi-etapas, incluindo design de triagem CRISPR, análise de RNA-seq de célula única, previsão ADMET e diagnóstico de doenças raras.