「engineering」の検索結果

Expert-level composites engineering covering fiber reinforced polymers, matrix materials, laminate theory, manufacturing processes, failure modes, and composite design.

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Expert-level ceramics covering ceramic bonding, processing, mechanical properties, thermal properties, electronic ceramics, and ceramic applications in engineering.

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Expert-level control systems engineering covering feedback control, PID design, root locus, frequency domain methods, state-space design, and digital control.

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Expert-level communications engineering covering modulation, channel capacity, error correction, wireless systems, OFDM, MIMO, and 5G technologies.

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Perform a dual-lens critical review of the specification and plan from both product strategy and engineering risk perspectives before implementation.

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React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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Translate an image brief into provider-specific prompt grammar per model. Use when writing or refining an image-generation prompt for Ideogram, Flux, Gemini, GPT Image 2, or Recraft.

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Use when designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.

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Use when designing engineering 1:1s — cadence, agenda mix, growth-vs-blocker-vs-trust shape, cancellation anti-patterns. Triggers on 'fix my 1:1s', 'should I cancel 1:1s this week'.

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Use when shaping an engineering hiring loop — stages, take-home vs live, calibration, bar-raiser, signal-vs-noise audit. Triggers on 'design our interview loop', 'audit our hiring bar'.

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Use when sequencing a launch — alpha / beta / GA waves, audience-by-wave logic, narrative beats per wave, engineering-readiness gates. Triggers on 'plan the launch', 'sequence GA'.

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Padrões pragmáticos de codificação - conciso, direto, sem over-engineering, sem comentários desnecessários

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Guia especializado em padrões de engenharia de prompts, melhores práticas e técnicas de otimização. Use quando o usuário quer melhorar prompts, aprender estratégias de prompting ou depurar comportamento de agentes.

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Controle saída de LLM com regex e gramáticas, garanta geração válida de JSON/XML/código, aplique formatos estruturados e construa fluxos de trabalho multi-etapas com Guidance - framework de geração restrita da Microsoft Research

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Extraia dados estruturados de respostas de LLM com validação Pydantic, tente novamente automaticamente extrações que falharem, analise JSON complexo com segurança de tipo e transmita resultados parciais com Instructor - biblioteca de saída estruturada testada em batalha

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Garanta estrutura válida de JSON/XML/código durante a geração, use modelos Pydantic para outputs type-safe, suporte modelos locais (Transformers, vLLM) e maximize velocidade de inferência com Outlines - biblioteca de geração estruturada da dottxt.ai

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Domine técnicas avançadas de engenharia de prompts para maximizar o desempenho, confiabilidade e controlabilidade de modelos de linguagem.

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Operações de LLM — RAG, embeddings, bancos de dados vetoriais, fine-tuning, prompt engineering avançado, custos de LLM, avaliações de qualidade e arquiteturas de IA para produção.

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Construa sistemas de ML em produção com PyTorch 2.x, TensorFlow e frameworks modernos de ML. Implementa model serving, feature engineering, A/B testing e monitoramento.

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Write minimal, accessible web UI without over-engineering, adapting to whatever stack the project uses — React, Vue, Svelte, Angular, web components, or plain HTML. Use this skill on every project and every task that writes or reviews markup or components, builds forms, adds interactive elements like buttons, dialogs, accordions, or tabs, or audits code for accessibility — even when the user never mentions accessibility, and even inside a framework, CMS, or design system. It's non-negotiable regardless of project type, stack, or deadline. About to reach for ARIA attributes, a dialog library, a focus-trap package, or a headless UI component? Use this skill first.

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[General] Use when you need to (re)generate a DERIVED navigation index, cross-capability ERD, or reimplementation guide assembled FROM the canonical Feature Specs under docs/specs/**. Never extracts a separate A-E engineering tree.

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[Utilities] Use when recording an engineering journal entry — capture decisions, blockers, lessons, or progress notes during work.

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Design, implement, and integrate generalized validation harnesses across a producer-consumer boundary after a local harness contract exists. Use when refactoring custom validation CLIs/MCPs for large polyrepos, extending Steward across sibling repos, or deploying a local tool to a consumer project for dogfooding and testing; use mcp-harness-repo-maintainer first for initial steward.yaml adoption and cold-start proof.

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Establish or audit a structural quality contract for any agent-operated engineering repository: app, library, CLI/tool, plugin, harness, or meta repo. Use when a repo needs charter clarity, docs/decision ownership, type-native validation gates, evidence paths, safe action policy, cold-start legibility, maturity proof, repair-loop routing, consumer/producer owner-boundary routing, command surface evolution, evolutionary simplicity (see references/evolutionary-simplicity.md), or a repo ecology pass to decide what should be compressed, merged, removed, updated, created, retired, or moved to checks.

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