リサーチ・学習のスキル

Agentes autônomos são sistemas de IA que conseguem decompor objetivos, planejar ações, executar ferramentas e se auto-corrigir sem orientação humana constante. O desafio não é torná-los capazes - é torná-los confiáveis. Cada decisão extra multiplica a probabilidade de falha. Esta habilidade cobre loops de agentes (ReAct, Plan-Execute), decomposição de objetivos, padrões de reflexão e confiabilidade em produção. Insight-chave: taxas de erro compostas matam agentes autônomos. Uma taxa de sucesso de 95% por passo cai para 60% b

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Skill de pesquisa profunda alimentado por NotebookLM MCP. Conduz pesquisa estruturada em múltiplas fontes (análise de mercado, inteligência competitiva, análise de tendências, pesquisa de prospects) usando Google NotebookLM como mecanismo de pesquisa, depois entrega briefs formatados e artefatos opcionais de estúdio (slides, podcasts de áudio, vídeos, infográficos, relatórios, mapas mentais).

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Sistemas de memória persistente para conversas com LLM, incluindo memória de curto prazo, longo prazo e baseada em entidades. Use quando: memória de conversa, lembrar, persistência de memória, memória de longo prazo, histórico de chat.

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Estratégias para gerenciar janelas de contexto de LLMs, incluindo sumarização, recorte, roteamento e prevenção de degradação de contexto. Use quando: janela de contexto, limite de tokens, gerenciamento de contexto, engenharia de contexto, contexto longo.

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Construa agentes de IA que interagem com computadores como humanos fazem - visualizando telas, movimentando cursores, clicando botões e digitando texto. Cobre Computer Use da Anthropic, Operator/CUA da OpenAI e alternativas de código aberto. Foco crítico em sandboxing, segurança e tratamento dos desafios únicos do controle baseado em visão. Use quando: computer use, automação de desktop agent, controle de tela IA, agente baseado em visão, automação de GUI.

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[Workflow] Use when activating the Research & Synthesis workflow — research a topic via web sources, then synthesize per --output={synthesis|business-eval|marketing|course} (knowledge report, business evaluation, marketing strategy, or course material).

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[Architecture] Use when you need to research, analyze, and compare tech stack options as a solution architect.

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[Research] Use when starting a web research task — discover, gather, and triage candidate sources on a topic to feed deeper investigation.

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[Planning] Use when you need to research, analyze, and plan technical solutions that are scalable, secure, and maintainable.

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[Research] Use when you need to review knowledge artifacts for completeness, citation quality, confidence accuracy, and template compliance.

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[Research] Use when you need to synthesize research findings into structured report using template.

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[Utilities] Use when you need to teach Claude lessons that persist across sessions.

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[Quality] Use when you need to research and configure code quality tooling for any tech stack — linters, formatters, static analysis, pre-commit hooks, and CI gates.

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[Research] Use when you need to analyze market landscape: competitors, sizing (TAM/SAM/SOM), trends, SWOT, customer segments.

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[Planning] Use when you need to start a new project from scratch with full waterfall inception — idea, research, domain modeling, tech stack, and implementation plan.

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[Content] Use when you need to build structured learning/teaching course material with Bloom taxonomy objectives, modules, lessons, exercises, and assessments.

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[Research] Use when deeply researching top sources from web-research.

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Converts structured prospect research into concise outreach preparation briefs. Use when the user provides prospect or account research and wants a brief with context, angles, and claims to verify. It generates a research brief and must not invent personalization or send outreach.

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Designs an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads. Use when the user wants a repeatable lead workflow plan rather than a single source plan.

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Turns an ICP or research goal into a plan for finding and scraping suitable directories. Use when the user has a target audience but is unsure where to find them, and wants source categories, queries, and an extraction workflow.

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Compares a group of companies by products, positioning, market focus, and differentiators. Use when the user provides several company records and wants a structured competitive comparison.

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Turns company records into structured company research summaries. Use when the user provides company names or records and wants a consistent overview, market position, and relevance assessment.

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Creates a repeatable process for researching and comparing companies. Use when the user wants a structured, reusable company-research workflow with objectives, sources, fields, and validation.

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Identifies missing information required to complete qualification, segmentation, or outreach preparation. Use when the user provides records and a goal and wants prioritized research gaps with sources.

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