「wing design」の検索結果

Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.

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Expert in building portfolios that actually land jobs and clients - not just showing work, but creating memorable experiences. Covers developer portfolios, designer portfolios, creative portfolios, and portfolios that convert visitors into opportunities. Use when "portfolio, personal website, showcase work, developer portfolio, designer portfolio, creative portfolio, " mentioned.

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Suede AI eval design and coverage audit: AI-SPEC, failure-mode rubric with severity scoring, concrete pass/fail eval cases, coverage and infrastructure scores, and mechanical acceptance gates. Use when a change ships LLM, RAG, agent, classifier, prompt, or generated-media behavior, or when asked to write evals for an AI feature, design test cases for a model surface, audit existing eval coverage, or judge whether AI behavior is safe to ship. No AI-SPEC means no eval plan, and no eval plan holds the recommended ship verdict. NOT FOR: reviewing or grading the implementation code behind the AI surface (use suede-code); wiring a passing suite into CI as a required check (use suede-ci-gate); UAT of the built feature beyond the eval suite (a private Suede Labs companion, not in this pack).

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Use when a screen design needs variants - how many, one document per variant, what makes two variants genuinely different, recommending one, how the human's choice is read, and narrowing to the chosen one in revision

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UI/UX design intelligence with searchable style, palette, typography, and chart databases. Use when designing UI components, choosing colors/fonts, reviewing code for UX issues, building landing pages, or implementing responsive layouts.

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Guides writing, reviewing, and reasoning about modern Android UI code using Jetpack Compose. Covers best practices for state management, side effects, recomposition, navigation, Material 3 design, accessibility, and performance. Use when reading, writing, or reviewing any Jetpack Compose project.

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Use before generating, editing, or reviewing any user interface — a dashboard panel, a landing page, an email, a slide, an app screen. Sets three deliberate design dials (variance, motion, density) BEFORE generation so the output has a point of view instead of defaulting to the timid, uniform look that reads as "AI made this". Applies to Genesis's OWN dashboard UI, not only things built for others.

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Designs and audits native iOS interfaces. Use when reviewing or refining SwiftUI layout, typography, Liquid Glass, navigation, or dashboards on a freshly verified build.

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Designs and audits native Android interfaces. Use when reviewing Compose layout, typography, color, motion, or adaptive patterns on a verified emulator build.

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Analyze and design control flows and data structures. Produces compact ASCII tree diagrams showing triggers, call chains, payload shapes, state mutations, and re-render effects. Use when user asks to diagram, trace, visualize, or design a flow or data structure.

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Designing and reviewing APIs: OpenAPI spec generation, versioning strategy, breaking change detection, REST/GraphQL best practices. Use for API design or OpenAPI specs.

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Audit and redesign AI-generated feedback for pedagogical quality, timing, and learning impact. Use when building or reviewing automated feedback in digital learning tools.

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Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.

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Reviews Rust code for ownership, borrowing, lifetime, error handling, trait design, unsafe usage, and common mistakes. Use when reviewing .rs files, checking borrow checker issues, error handling patterns, or trait implementations. Covers Rust 2024 edition patterns and modern idioms.

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Helper text, placeholders, validation and submit behaviour. Use when designing or reviewing a form, input field or data entry UI.

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Foundations of digital signal processing — sampling, aliasing, the Nyquist criterion, quantization, convolution, the discrete Fourier transform, FFT, FIR and IIR filter design, windowing, spectral leakage, and practical issues in fixed-point versus floating-point implementation. Use when designing filters, analyzing spectra, choosing sample rates, reasoning about aliasing, or implementing DSP algorithms on a microcontroller, DSP chip, or host CPU.

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Distributed storage systems design and operation for cloud platforms. Covers the GFS/HDFS block-and-master pattern, object storage (Swift/S3) with consistent hashing and eventual consistency, block storage semantics, replication vs erasure coding, the CAP theorem in practice, read-repair and anti-entropy, snapshot chains, and the GFS/BigTable/Spanner evolution. Use when designing a storage subsystem, choosing between object/block/file, or reviewing a replication and consistency strategy.

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Identity, authentication, authorization, and token management for cloud platforms. Covers Keystone-style scoped tokens, OAuth 2.0 flows, OpenID Connect, JWT structure and pitfalls, federation with SAML/OIDC, service-to-service auth with mTLS and SPIFFE, principle of least privilege, IAM role design, and the service catalog pattern (public/internal/admin endpoints). Use when designing authn/authz for a multi-tenant cloud service, integrating with an identity provider, or reviewing IAM policies for over-privilege.

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Networking fundamentals as they apply to cloud infrastructure — virtual networks, subnets, routers, NAT, floating IPs, security groups, VLAN/VXLAN segmentation, load balancing, SDN concepts, and how Neutron-style cloud networks sit on top of physical topology. Covers TCP behavior at scale, congestion control, tail latency, overlay networks, and the operational gotchas that come from network layering. Use when designing cloud network topology, debugging cross-AZ latency, or reviewing a proposed VPC/SG design.

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Design engineering principles for making interfaces feel polished. Use when building UI components, reviewing frontend code, implementing animations, hover states, shadows, borders, typography, micro-interactions, enter/exit animations, or any visual detail work. Triggers on UI polish, design details, "make it feel better", "feels off", stagger animations, border radius, optical alignment, font smoothing, tabular numbers, image outlines, box shadows.

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Specifies best practices, including following RESTful API design principles, implementing responsive design, using Zod for data validation, and regularly updating dependencies. This skill promotes modern coding standards and helps developers write consistent, maintainable code.

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Generate probability-weighted alternative options that challenge default thinking. Forces unconventional alternatives and exposes hidden assumptions behind the "obvious" choice. For decision-point analysis, NOT full design exploration. Triggers on "대안", "alternatives", "옵션 뽑아", "options", "어떤 방법이", "아이디어", "다른 방법", "선택지".

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Use when the user is deciding, reviewing, or second-guessing a software architecture or tech-stack choice — monolith vs microservices vs serverless vs event-driven, backend language, database type, caching, CQRS/event sourcing, polyglot, or a migration like Strangler Fig. Triggers on "should I use microservices", "which database", "tech stack for", "system design", or "architecture review". For how to deploy, operate, and scale that design (CI/CD, cloud, Kubernetes, IaC), use devops.

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Conduct a peer review of research methodology, experimental design, and manuscript quality. Covers methodology evaluation, statistical appropriateness, reproducibility assessment, bias identification, and constructive feedback. Use when reviewing a manuscript, preprint, or internal research report, evaluating a research proposal or study protocol, assessing evidence quality behind a claim, or reviewing a thesis chapter or dissertation section.

日本語の概要は準備中です。原文の説明を表示しています。